Monitoring Land Degradation Research Articles

Monitoring land degradation risk using ASTER data: The non-evaporative fraction as an indicator of ecosystem function

There is a need to develop operational land degradation indicators for large regions to prevent losses of biological and economic productivity. Disturbance events press ecosystems beyond resilience and modify the associated hydrological and surface energy balance. Therefore, new indicators for water-limited ecosystems can be based on the partition of the surface energy into latent ( λE) and sensible heat flux ( H). In this study, a new methodology for monitoring land degradation risk for regional scale application is evaluated in a semiarid area of SE Spain. Input data include ASTER surface temperature and reflectance products, and other ancillary data. The methodology employs two land degradation indicators, one related to ecosystem water use derived from the non-evaporative fraction (NEF = H / ( λE + H)), and another related to vegetation greenness derived from the NDVI. The surface energy modeling approach used to estimate the NEF showed errors within the range of similar studies ( R 2 = 0.88; RMSE = 0.18 (22%)). To create quantitative indicators suitable for regional analysis, the NEF and NDVI were standardized between two possible extremes of ecosystem status: extremely disturbed and undisturbed in each climatic region to define the NEFS (NEF Standardized) and NDVIS (NDVI Standardized). The procedure was successful, as it statistically identified ecosystem status extremes for both indicators without supervision. Evaluation of the indicators at disturbed and undisturbed (control) sites, and intermediate surface variables such as albedo or surface temperature, provided insights on the main surface energy status controls following disturbance events. These results suggest that ecosystem functional indicators, such as the NEFS, can provide information related to the surface water deficit, including the role of soil properties.

Integration of herder knowledge and ecological methods for land degradation assessment around sedentary settlements in a sub-humid zone in northern Kenya

The debate on land degradation and desertification associated with sedentarisation of pastoral communities in the Sahelian zone remains contentious. Discussions of land degradation from the perspective of local communities shapes human perceptions where local peoples' narratives provide personal experiences of environmental change. Local community participation in assessing and monitoring land degradation around pastoralist settlements has important implications for implementation of the Global Convention on Combating Desertification (CCD) and the Convention on Biological Diversity (CBD). Previously, ecologists assessed impacts on the vegetation, while herders were hardly involved. In this study, we integrated indigenous knowledge of herders and ecological methods (IKEM) to assess the impacts of sedentarisation on vegetation in a sub-humid zone in northern Kenya. Degradation of vegetation around two settlements 10 to 30 years old was inferred from herder knowledge of land-use history, perception of environmental change and joint assessments of vegetation change radiating from settlements compared to the benchmark (a forest reserve). Despite the high stocking densities near settlements and the history of continuous grazing, there was no evidence of vegetation cover loss. Rather, bush cover had increased, while palatable grass species had declined. Herders blamed official banning of fires, episodic rainfall and grazing pressure for the change. From the herders' perspective, changes in vegetation structure and composition reduced land-use suitability for livestock production; while from an ecological perspective, overall classical land degradation was not confirmed. The differences could influence utility of the land. The paper discusses the results in the wider context of global environmental conventions using the IKEM framework.

Land degradation monitoring using multi‐temporal Landsat TM/ETM data in a transition zone between grassland and cropland of northeast China

Land degradation is one of the most pressing problems of environments. This research presents a methodology to monitor land degradation in a transition zone between grassland and cropland of northeast China, where soil salinization and grassland degradation, even desertification, have been observed in the past few decades. Landsat TM/ETM data in 1988, 1996 and 2001 were selected to determine the rate and status of grassland degradation and soil salinization together based on both decision tree (DT) classifier and the field investigation. The thermal radiance values of TM/ETM 6 data, the Normalized Difference Vegetation Index (NDVI), and new variables (brightness, greenness, and wetness) generated by the Kauth–homas Transforms (KT) algorithms from Landsat TM/ETM data served as the feature nodes of a DT classifer and contributed to improving the classification results. It showed an overall accuracy of more than 85% and a Kappa statistic of agreement of about 0.79 in 1996 and 2001 with the exception of about 0.69 in 1988. The statistical areas of land degradation in the observation periods revealed that land degradation, especially the salt‐affected soil, is accelerating. The distribution maps of land degradation in the years of 1988, 1996 and 2001 were generated respectively based on the classification results. Their change maps were created by the difference between the distribution maps from 1988 to 1996 and from 1996 to 2001 respectively. The changes of salt‐affected soil occurred near the water bodies due to variations of water sizes, and most of the degraded grassland appeared around the salt‐affected soil. Although climate variations play an important role in this region, human activities are also crucial to land degradation.

Monitor Land Degradation Phenomena Through Landscape Metrics and NDVI: Gordes, Kavacik, Ilicak, Kumcay and Marmara Lake Basins (Turkey)

Monitor Land Degradation Phenomena Through Landscape Metrics and NDVI: Gordes, Kavacik, Ilicak, Kumcay and Marmara Lake Basins (Turkey)

Imaging spectroscopy of changing Earth's surface: a major step toward the quantitative monitoring of land degradation and desertification

Imaging spectroscopy makes direct identification of surface materials possible in a spatial context based on diagnostic visible and near-infrared properties. Advanced methodologies permit the deconvolution of complex surface signatures. It opens a number of possibilities for characterizing and monitoring mineralogical and/or biogeochemical surface properties and changes, particularly in the field of land desertification, where understanding of processes involve the quantitative description of the interplay between soils and vegetation components. To cite this article: P.C. Pinet et al., C. R. Geoscience 338 (2006).

Mapping and monitoring land degradation risks in the Western Brazilian Amazon using multitemporal Landsat TM/ETM+ images

AbstractMapping and monitoring land degradation in areas under human‐induced stresses have become urgent tasks in remote sensing whose importance has not yet been fully appreciated. In this study, a surface cover index (SCI) is developed to evaluate and map potential land degradation risks associated with deforestation and accompanying soil erosion in a Western Brazilian Amazon rural settlement study area. The relationships between land‐use and land‐cover (LULC) types and land degradation risks as well as the impacts of LULC change on land degradation are examined. This research indicates that remotely sensed data can be effectively used for identification and mapping of land degradation risks and monitoring of land degradation changes in the study area. Sites covered by mature forest and advanced successional forests have low land degradation risk potential, while some types of initial successional forests, agroforestry/perennial agriculture and pasture have higher risk potential. Deforestation and associated soil erosion are major causes leading to land degradation, while vegetation regrowth reduces such problems. Copyright © 2006 John Wiley & Sons, Ltd.

Separating grassland and shrub vegetation by multidate pixel‐adaptive spectral mixture analysis

Monitoring and assessment of land degradation and the processes driving it require effective change indicators at appropriate scales and spatial extent. In this context, the decomposition of Mediterranean rangeland vegetation into woody and herbaceous fractions is of great significance. This study demonstrates that a stratification of vegetation into woody and herbaceous components is possible with two satellite images of moderate spatial and spectral resolution. We used a pixel‐adaptive spectral mixture analysis to derive subpixel‐level vegetation abundances from satellite imagery representing two specific phenological stages of Mediterranean rangeland vegetation. The transferability of endmember models is often a problem of multidate spectral mixture analysis because of uneven spectral dimensionality within and among datasets. In our approach, the dimensionality of the mixture model was determined automatically, based on error calculations. This method enables the transfer of the mixture model to multiple scenes and allows for quantitative comparison of vegetation abundances. The results show that the woody vegetation fraction corresponds well with field data (R 2 = 0.76–0.91) and vegetation cover mapped from a very high resolution satellite image. The herbaceous vegetation fraction displays a good correlation compared to field mapped cover but still implies a moderate level of uncertainty (R 2 = 0.52–0.76). The approach pursued in this research may be valuable for the characterization of rangeland plant communities and for the derivation of vegetation‐related indicators useful for the monitoring and assessment of degradation.

Land degradation assessment in Southern Africa: integrating local and scientific knowledge bases

AbstractRecent attempts to address land degradation have seen calls for greater integration of scientific expertise with local knowledges. In this paper we investigate the potential for such combined understandings to enhance the accuracy, coverage and relevance of land degradation assessment. We followed a participatory approach, using methods from a variety of disciplines, to elicit potential land degradation indicators from communities in Botswana and Swaziland. These indicators were then assessed according to local and scientific understandings. We noted a significant overlap between scientific and local knowledges about land degradation in most instances. Where discrepancies occurred, the integrated participatory approach we used allows appropriate explanation to be reached, supporting the case that such an iterative process can lead to both accurate and relevant monitoring of land degradation. However, the incorporation of integrated knowledges into national policy has not been widespread in either country, suggesting that much greater efforts are required to institutionalise participatory land degradation assessment methodologies. Powerful, often neo‐Malthusian narratives of degradation continue to dominate policy discourse and limit the extent to which hybrid combined local and scientific knowledges can enhance land degradation assessment on a national and regional scale. Copyright © 2006 John Wiley & Sons, Ltd.

Land Degradation in the Heihe River Basin in Relation to Plant Growth Conditions

Land degradation is a crucial issue in semi-arid and arid areas. The Heihe River basin is the second largest inland river basin in the arid regions of Northwest China. Land degradation is a serious passive problem for the socioeconomic development in this region. In this paper, we develop a land degradation model. Land Degradation Index (LDI), which integrates the main factors influencing land degradation. The factors are mainly those related to plant growth conditions: precipitation, potential evapo-transpiration (PE), vegetation fraction cover, slope and aspect, soil type, and land cover. We find that our model can be used to effectively monitor land degradation over this region.

Land Degradation Monitoring in Namibia: A First Approximation

This paper presents development of a first approximation of a Namibian, national level, land degradation monitoring system. The process involved a large number of stakeholders and led to the definition of four primary indicators that were regarded as related to land degradation in Namibia: population pressure, livestock pressure, seasonal rainfall and erosion hazards. These indicators were calculated annually for the period 1971-1997. Annual land degradation risk maps were produced for the same period by combining the indicators. A time series analysis of results generated by indicators was undertaken at two sites. The analysis revealed a general trend towards an increased land degradation risk over the period 1971-1997. A decrease in annual rainfall and an increase in livestock numbers caused this negative trend at one site, while decreased annual rainfall and increased human population were the causes at a second site. Evaluation of resulting maps through direct field observations and long-term monitoring at selected study sites with different conditions relevant for the indicators defined, is an essential next step.

Using satellite remote sensing data to detect land use/cover changes and to monitor land degradation in central Jordan.

Using satellite remote sensing data to detect land use/cover changes and to monitor land degradation in central Jordan.

Applications of soil and plant analyses in identification and amelioration of land degradation

The raised consciousness of society to the condition of natural resources has increased the need to quantify the possible degradation of these resources due to resource use and management operations. A common expectation is that a test analysis is simple, conducted quickly at low cost and provides accurate and quantitative results for decision making. Often this expectation is not met due to the separation of analytical services from interpretative guidelines and the understanding of systems. The deciding factors for the continued use of analytical services in the future will be the meaningfulness of the analysis result, the cost and complexity of the analysis and the ability to provide useful interpretations of the data. Greater emphasis is now being placed on analytical results to assist the reversal of land degradation. Land degradation is taken to mean a reduction in the potential productivity of an area, or of a natural or modified ecosystem in relation to its natural or preferred state. Thus the meaning of land degradation is considered within an ecosystem context rather than a specific spatial or temporal value at one point or across a paddock. This paper discusses the meaning of land degradation and examines the weaknesses in a number of commonly used analyses for estimating and evaluating land degradation. We propose an ecosystem conceptual framework to evaluate the utility of analyses and the appropriate derivation of interpretive guidelines. A range of common analyses used for land degradation are evaluated against selected criteria using a multi‐objective decision framework to rate the value of the analysis in identifying and monitoring land degradation

Monitoring land degradation in the semiarid tropics using an inferential approach: the Kabomo basin case study, Nigeria

Lack of baseline data on soil fertility status for most semiarid areas to a very large extent hampers the success of land degradation monitoring. However, this can be overcome by adopting an inferential approach which presupposes that soils of an area of uniform geologic, geomorphic and climatic characteristics differ mainly because of the uses to which they are put. On this basis, soil conditions of a long-standing vegetation community can be used to assess the extent of soil changes resulting from land-use practices, provided that both the vegetation community and the land-use plots are located in an area having the uniform environmental parameters noted above. This approach was adopted in the Kabomo area of Nigeria, a typical semiarid tropical ecosystem, to monitor the extent of soil degradation resulting from 20 years (1972–92) of arable farming, livestock ranching and legume grass farming. Using a systematic sampling procedure, topsoil (0–15 cm) and subsoil (20–30 cm) samples were collected from both the long-standing vegetation community plot (over 80 years old) which was chosen to serve as the control, and the three land-use plots. The collected samples were then analysed for texture, bulk density, water content, water stable aggregates greater than 0·50 mm, organic matter, pH, cation exchange capacity (CEC), total nitrogen, available phosphorus and exchangeable bases. The mean value of every property for each plot was then divided by the mean value of the same property for the control plot in order to assess the extent of change (i.e. extent of degradation) in the property. The Student's t-test was then used to assess the significance of such a change. The results obtained revealed that, in general, the mean values of the various soil properties, with the exception of sand and bulk density, have declined by between 3 per cent and 72 per cent, and in most cases the declines are statistically significant. Sand and bulk density, on the other hand, show some increases of between 6 per cent and 78 per cent, though only the increase in respect of the sand fractions are statistically significant. Similarly, it was observed that the extent of degradation was much greater under the arable land and least under the livestock ranching plot. The potential causes of these trends were discussed, while suggestions were offered on how best to utilize this approach in carrying out effective monitoring of land resources in the semiarid tropics. © 1997 John Wiley & Sons, Ltd.

Mapping environmental carrying capacity using an artificial neural network: A first experiment

AbstractThe economic development activities of an increasing world population threaten the assimilative capacity of our environment and have stimulated interest in the concept of environmental carrying capacity. While the pace of land transformations has encouraged the refinement of information technologies such as satellite remote sensing to provide a synoptic view of earth‐system processes, the volume of information these systems generate and the high level of expertise required to translate these data retard effective and timely land‐management decision making. This paper introduces a methodology that employs an artificial neural network trained to recognize categories of population support capacity from satellite data acquired from the NOAA‐AVHRR. The network, functioning as an ‘intelligent’ mapping tool, achieved a classification accuracy of 77.5 per cent for the study site and points to the potential role a model of this type may play in land degradation monitoring.

Use of earth observation satellite data for land degradation mapping and monitoring in Mediterranean ecosystems: Towards a satellite-observatory

The degradation of the permanent seminatural vegetation and the resulting acceleration of soil degradation and erosion processes constitute major elements of land degradation in the Mediterranean basin. Given the European Commission's interest in mapping and controlling desertification phenomena in the Mediterranean member states, the "Environmental Mapping and Modelling Unit" (EMAP) of the Joint Research Centre is investigating possibilities for using operational earth observation satellites for mapping and repeated monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches have been developed that can already be routinely applied to large regions. This paper discusses the problems of standardized retrieval of remotely sensed primary parameters (such as reflectance), concepts relating to the thematic interpretation of reflectance data, and the definition of satellite-derived degradation indices. In addition, this paper presents requirements for designing an operational satellite observatory for monitoring Mediterranean land degradation.

Land degradation, soil erosion and desertification monitoring in Mediterranean ecosystems

Abstract Under the European Commissions's DG XII “Research & Development Programme in the Field of the Environment” emphasis is given to identify, map and control desertification phenomena in the Mediterranean area. Based upon previous experiences in Mediterranean land cover mapping, the “Environmental Mapping and Modelling Unit” of the Institute for Remote Sensing Applications is actively participating in this programme. A semi‐operational approach to land degradation mapping has recently been developed which requires radiometric rectification of the multi‐spectral images and the availability of spectral libraries. Linear spectral mixture modelling is then used to decompose image spectra into their spectrally distinct components, the fractional abundance of which then provides a largely unbiased measure for direct mapping of vegetation abundance and the identification of soil conditions and erosion hazards. Ground verification in a well‐controlled test site in the south of France proved an excellent accuracy in identifying soil degradation levels with both airborne imaging spectrometry (AVIRIS) and Landsat TM data. The same method with identical processing parameters was then applied to Thematic Mapper images from a different Mediterranean region (Peloponnesos, Greece). Results confirmed the experiences of the first study site, thereby suggesting that the approach holds the potential for operational applications, including monitoring of erosion processes and changes in vegetation cover (desertification monitoring).

International activities in assessing and monitoring soil degradation

AbstractThe problem of land degradation is not new, but never before has it been so widespread or affected the lives of so many people. The need for a global assessment of land degradation was highlighted by the United Nations Conference on the Human Environment in 1972. Since then, several attempts have been made to develop methodologies that will allow for systematic assessment and monitoring of global land degradation. Systematic work started in 1975, when FAO and United Nations Environment Programme (UNEP) collaborated in a study to develop a provisional method for soil degradation. This method was tested, and maps on a scale of 1:5,000,000 were produced for North Africa and the Near East. However, the method proved difficult to apply accurately, so this project was followed by another where the method was revised and refined in an effort to assess and map desertification. Again, problems were encountered because of the complexity of the subject and the lack of usable reliable data. More recently, ISRIC, using a simplified methodology and the assistance of some 250 scientists from around the world, has produced a world map of human induced soil degradation at a scale of approximately 1:10,000,000. Meanwhile, interest has been growing in the problem of nutrient depletion in developing countries and a study has been completed of N, P and K balances in the soils of 38 African countries. Although we still do not have an accurate assessment of global land degradation and no systematic monitoring is yet in place, these innovative studies have provided us with a sound basis for future work and have identified many of the practical problems of measuring land degradation, data collection and analysis that will have to be overcome before more accurate assessment and monitoring can be achieved.

SALTMAP — Airborne EM for the Environment

There is increasing recognition that electrical conductivity is an important diagnostic parameter of the near-surface in the applications of land degradation monitoring, ground-water exploration and geological mapping. Airborne electromagnetic (AEM) geophysical surveys provide a means of measurement of ground-conductivity distributions. SALTMAP, a new AEM survey system being developed in Australia by World Geoscience Corporation and the CSIRO Divisions of Exploration Geoscience and Water Resources, has been designed specifically to make high-resolution measurements of the conductivity distribution within the regolith. This results from the broadband nature of the transmitter and receiver antennae and high-speed signal processing incorporated in SALTMAP. SALTMAP will record secondary fields at frequencies in excess of 50 kHz ? unprecedented for a broadband AEM system ? enabling measurement of near-surface conductivity distributions. In resistive terrain, SALTMAP's specifications give it a unique ability to discriminate mineral exploration targets to some depth. As a result of the broad bandwidth of SALTMAP, it is susceptible to a wide range of interference problems which can be overcome only with powerful signal processing equipment that has only recently become available. A three-component receiver antenna has been incorporated in SALTMAP to provide full measurement of the secondary field. All SALTMAP components are under the control of flexible computer algorithms to enable SALTMAP to be adapted to a wide range of applications in a wide range of conditions. SALTMAP provides a powerful new tool for land and water resource authorities and mineral explorers. It will provide detailed information about the hydrogeology over large areas at a fraction of the cost of normal land treatments. Improved interpretation of regolith conditions will result in a significant increase in efficiency of implementation of strategies for sustainable land use and rehabilitation.