Paula D. Blanco

Remote Sensing of Land Degradation: Experiences from Latin America and the Caribbean

Land degradation caused by deforestation, overgrazing, and inappropriate irrigation practices affects about 16% of Latin America and the Caribbean (LAC). This paper addresses issues related to the application of remote sensing technologies for the identification and mapping of land degradation features, with special attention to the LAC region. The contribution of remote sensing to mapping land degradation is analyzed from the compilation of a large set of research papers published between the 1980s and 2009, dealing with water and wind erosion, salinization, and changes of vegetation cover. The analysis undertaken found that Landsat series (MSS, TM, ETM+) are the most commonly used data source (49% of the papers report their use), followed by aerial photographs (39%), and microwave sensing (ERS, JERS-1, Radarsat) (27%). About 43% of the works analyzed use multi-scale, multi-sensor, multi-spectral approaches for mapping degraded areas, with a combination of visual interpretation and advanced image processing techniques. The use of more expensive hyperspectral and/or very high spatial resolution sensors like AVIRIS, Hyperion, SPOT-5, and IKONOS tends to be limited to small surface areas. The key issue of indicators that can directly or indirectly help recognize land degradation features in the visible, infrared, and microwave regions of the electromagnetic spectrum are discussed. Factors considered when selecting indicators for establishing land degradation baselines include, among others, the mapping scale, the spectral characteristics of the sensors, and the time of image acquisition. The validation methods used to assess the accuracy of maps produced with satellite data are discussed as well.

Radar remote sensing of wind-driven land degradation processes in northeastern Patagonia

Wind-driven land degradation negatively impacts on rangeland production and infrastructure in the Valdes Peninsula, northeastern Patagonia. The Valdes Peninsula has the most noticeable dunefields of the Patagonian drylands. Wind erosion has been assessed at different scales in this region, but often with limited data. In general, terrain features caused by wind activity are better discriminated by active microwaves than by sensors operating in the visible and infrared regions of the electromagnetic spectrum. This paper aims to analyze wind-driven land degradation processes that control the radar backscatter observed in different sources of radar imagery. We used subsets derived from SIR-C, ERS-1 and 2, ENVISAT ASAR, RADARSAT-1, and ALOS PALSAR data. The visibility of aeolian features on radar images is mostly a function of wavelength, polarization, and incidence angle. Stabilized sand deposits are clearly observed in radar images, with defined edges but also signals of ongoing wind erosion. One of the most conspicuous features corresponds to old track sand dunes, a mixture of active and inactive barchanoid ridges and parabolic dunes. This is a clear example of deactivation of migrating dunes under the influence of vegetation. The L-band data reveal details of these sand ridges, whereas the C-band data only allow detecting a few of the larger tracks. The results of this study enable us to make recommendations about the utility of some radar sensor configurations for wind-driven land degradation reconnaissance in mid-latitude regions.

Improving the discrimination of vegetation and landform patterns in sandy rangelands: a synergistic approach

Soil erosion is a key factor in land degradation processes in the sandy rangelands of the Peninsula Valdés of Patagonia, Argentina. Mapping landform and vegetation patterns is important for improving prediction, monitoring and planning of areas threatened by sand and shrub encroachment. This paper investigates the contribution of optical sensors, such as the Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and textural measures derived from microwave Radarsat Advanced Synthetic Aperture Radar (ASAR) to their discrimination. An evaluation is undertaken to compare the classification accuracy achieved by specific regions of the spectrum and their synergistic use in an object‐oriented approach. Image segmentation and object‐oriented classifications were applied to the datasets. This required defining appropriate fuzzy membership functions for characterizing active and stabilized lineal dunes and the main vegetation classes. Improvements in the discrimination of active and stabilized dunes (vegetated by either scrub or grass) were achieved by using an object‐oriented classification that integrated microwave and visible near‐infrared (NIR) data. Changes in surface roughness caused by different vegetation types stabilizing the dunes affected the radar backscattering. Whereas Radarsat enabled a clear separation of scrub‐stabilized dunes, Terra‐ASTER showed superior performance in the cartography of grass‐stabilized dunes. The synergistic use of microwave and visible and near‐infrared (VNIR) data yielded a substantial increase in the discrimination and mapping of landform/vegetation patterns.

Semi-automated mapping of burned areas in semi-arid ecosystems using MODIS time-series imagery

Understanding spatial and temporal patterns of burned areas at regional scales, provides a long-term perspective of fire processes and its effects on ecosystems and vegetation recovery patterns, and it is a key factor to design prevention and post-fire restoration plans and strategies. Standard satellite burned area and active fire products derived from the 500-m MODIS and SPOT are avail able to this end. However, prior research caution on the use of these global-scale products for regional and sub-regional applica tions. Consequently, we propose a novel algorithm for automated identification and mapping of burned areas at regional scale in semi-arid shrublands. The algorithm uses a set of the Normalized Burned Ratio Index products derived from MODIS time series; using a two-phased cycle, it firstly detects potentially burned pixels while keeping a low commission error (false detection of burned areas), and subsequently labels them as seed patches. Region growing image segmentation algorithms are applied to the seed patches in the second-phase, to define the perimeter of fire affected areas while decreasing omission errors (missing real burned areas). Independently-derived Landsat ETM+ burned-area reference data was used for validation purposes. The correlation between the size of burnt areas detected by the global fire products and independently-derived Landsat reference data ranged from R² = 0.01 - 0.28, while our algorithm performed showed a stronger correlation coefficient (R² = 0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.

Synergistic use of Landsat and Hyperion imageries for ecological site classification in rangelands

The synergistic use of multispectral and hyperspectral data is evaluated for discrimination and mapping of ecological sites in the Patagonian rangelands. The method proposed encompasses two steps. First, mixture tuned matched filtering and logistic regression analyses are used for Hyperion data processing to obtain ecological site probability images in the area covered by hyperspectral imagery. Second, neural networks are used to model the relationships between the spectral response patterns of Landsat and the probability images from Hyperion, and to extrapolate them to the entire study area.

Vegetation of Península Valdés: Priority Sites for Conservation

This chapter describes the main vegetation units of Peninsula Valdes at scale 1:250,000 with emphasis on relevant physiognomic and floristic characteristics. Based on photogrammetry (aerial photograph pairs 1:60,000) and ground check, 18 dominant singular plant species arrangements (vegetation units) were identified reflecting the variety of environmental conditions at a mesoscale (1:250,000) within Peninsula Valdes. At sites selected for ground check, floristic–physiognomic census including a complete floristic plant species list with the relative abundance of each species were performed. After that, censuses of species abundance were ordered by principal component analysis. The layer structure, the main life forms and the dominant species for each identified and mapped vegetation unit were described. Among them, we identified shrubby vegetation units at northern and central Peninsula Valdes and, grassy vegetation units at southern Peninsula Valdes. A map of vegetation units and some pictures of the most representative vegetation units complete the vegetation description. Moreover, this chapter includes a detailed description of the plant communities (resolution scale 1:1) characterizing four sites identified as priorities for ecosystem conservation. Priority sites for conservation are located in Salt marshes, Uplands and Plain Systems and Endorheic Basins. Some contrasts between conserved and degraded community states are also exemplified.

Soil Degradation in Peninsula Valdes: Causes, Factors, Processes, and Assessment Methods

In semiarid rangelands where the anthropogenic impact is currently increasing, as occurs in the rangelands of the Peninsula Valdes, the detrimental impacts of soil degradation on land resources became really dramatic. This chapter presents a review on the current knowledge of soil degradation in the Peninsula Valdes rangelands. Section 1 introduces the chapter, Sect. 2 focuses on soil degradation main processes, factors and causes, and Sect. 3 presents a review of soil degradation assessment methods and several soil degradation studies carried out since 1990 in the Peninsula Valdes region. Water and wind erosion are the degradation processes that are most strongly evidenced. Major causes of soil degradation are attributed to a combination of climatic and anthropic factors, with overgrazing being perceived to be a major factor. Four key causes associated with overgrazing in the Peninsula Valdes region rangelands are described: (1) Poor range management with respect to flock distribution and overstocking, (2) Limited access to information, (3) Top-down and largely ineffective government policy, and (4) Overdependence on grazing systems for sustained livelihoods. Assessment methods for assessing soil degradation include: expert judgment, remote sensing, productivity changes, field monitoring, pilot studies at farm level based on field criteria and expert opinion, and modeling.

Contribution of Open Access Global SAR Mosaics to Soil Survey Programs at Regional Level: A Case Study in North-Eastern Patagonia

The Japan Aerospace Agency (JAXA) recently released multi-temporal global SAR mosaics derived from a 4-year data acquisition project (2007–2010) of the Advanced Land Observing Satellite (ALOS) PALSAR, L-band at 25 m spatial resolution. These open access data sets could assist traditional soil surveys and/or digital soil mapping programs undertaken at regional and subregional scales. Through improving mapping accuracy and reducing fieldwork time, together with digital identification and classification of landscape types and geomorphic features, soil survey programs could be completed over extensive areas currently lacking reliable soil information. Argentina is a country that needs to establish operational digital soil mapping (DSM) initiatives to address challenges and potential solutions of soil surveys at detailed and semi-detailed scales. These efforts could provide useful soil information to complement or update existing soil survey data, and document methods and results. Although remote sensing has been recognized as an efficient technology to support data gathering and information generation for soil and terrain mapping, the Argentine national knowledge of how to operationalize these techniques is still incomplete. Limited research has been carried out on the potential of microwave remote sensing data for spatial estimation of different topsoil properties, excepting soil moisture. This chapter intends to narrow down this knowledge gap by assessing the potential of ALOS PALSAR image mosaics for identifying and mapping land covers, as soil cartographic base, or as a value-added layer for integration in thematic soil mapping. The chapter also analyses changes in L-band backscatter overtime, and their relation to land degradation processes. To this end, a test area covering the north-eastern Patagonia region was chosen for its diversity of geology, geomorphology, soil, and land use, as well as for the existing soil expertise and an ongoing regional soil-mapping project.

A remote sensing and fuzzy multi-objective linear programming approach to model impact of land management decisions on ecosystem services of rangelands

This paper presents an approach to explicitly determinate optimal stocking rates based on trade-offs between guanaco density and livestock grazing intensity on rangelands of Patagonia, Argentina. As sheep farming becomes less profitable in this region, farmers and ranchers need to focus on sustainable wildlife harvesting as alternative income generation. We developed a methodology for spatially-explicit assessment and mapping of stocking rates based on tradeoffs and synergies between ecosystem services and livestock grazing intensity on rangelands. Forage use for livestock production, carbon sequestration, wildlife conservation and soil erosion are the ecosystem services and disservices evaluated over a gradient of grazing intensity. We show how rangelands stocking rate determination can be converted into a multi-objective optimization problem that can be solved using a Fuzzy Multi-Objective Linear Programing (MOLP).