応用水文 = Applied hydrology

Remote sensing of heavy metal contamination of soils has been widely studied. These studies concentrate heavily on the hyperspectral reflectance of typical metals in soils and in plants measured either in situ or in the laboratory. The most used wavebands lie within the visible-near infrared portion of the spectrum, especially the red edge. In comparison, mid- and far-infrared wavelengths are used far less frequently. Hyperspectral data are optimized to suppress noises and enhance the signal of the targeted metals through spectral derivatives and vegetation indexing. It is found that only subtle disparity exists in spectral responses for some metals at a sufficiently high content level. Not all metals have their own unique spectral response. Their detection has to rely on their co-variation with the spectrally responsive metals or organic matter in the soils. The closeness of the correlation dictates the accuracy of prediction. Without any theoretical grounding, this correlation is site-specific. Various analytical methods, including stepwise multi-linear regression, partial least squares regression, and neural networks have been used to model metal content level from the identified spectrally sensitive bands and/or their transformed indices. Both the model and the explanatory variables vary with the metal under detection and the area from which in situ samples are collected. Despite the amply demonstrated feasibility of estimating several metals by a large number of authors, only a few have succeeded in mapping the spatial distribution of metals from HyMAP, HJ-1A and Hyperion images to a satisfactory accuracy using complex algorithms and after taking environmental variables into account. The large number of reported failures testifies the difficulty in the detection of heavy metals in soils and plants, especially when their concentration level is low. The reasons or factors responsible for the success or failure have not been systematically analyzed, including the minimal spectral resolution required.

Hyperspectral sensing of heavy metals in soil and vegetation: Feasibility and challenges

Drought indicators are proliferating, but with little consideration of which are most meaningful for describing drought impacts. A number of recent reviews
compare different drought indicators, but none assess which indicators are actually used in the many operational drought monitoring and early warning efforts,
why they were selected, or whether they have been ‘ground-truthed,’ i.e., compared with information representing local drought conditions and/or impacts. Also lacking is a comprehensive assessment of the state of monitoring of drought impacts. To help fill this gap, we combine a review of drought indicators and impacts with a survey of 33 providers of operational drought monitoring and
early warning systems from global to regional scales. Despite considerable variety the indicators used operationally, certain patterns emerge. Both the literature
review and the survey reveal that impact monitoring does exist but has rarely been systematized. Efforts to test drought indicators have mostly focused on agricultural drought. Our review points to a current trend towards the design and use of composite indicators, but with limited evaluation of the links between indicators and drought impacts. Overall, we find that much progress has been
made both in research and practice on drought indicators, but monitoring and early warning systems are not yet strongly linked with the assessment of wider impacts on the environment and society. To understand drought impacts
fully requires a better framing of drought as a coupled dynamic between the environment and society.

Drought indicators revisited: the need for a wider consideration of environment and society

Towards the need for sustainable development, remote sensing (RS) techniques in the Visible-Near Infrared–Shortwave Infrared (VNIR–SWIR, 400–2500 nm) region could assist in a more direct, cost-effective and rapid manner to estimate important indicators for soil monitoring purposes. Soil reflectance spectroscopy has been applied in various domains apart from laboratory conditions, e.g., sensors mounted on satellites, aircrafts and Unmanned Aerial Systems. The aim of this review is to illustrate the research made for soil organic carbon estimation, with the use of RS techniques, reporting the methodology and results of each study. It also aims to provide a comprehensive introduction in soil spectroscopy for those who are less conversant with the subject. In total, 28 journal articles were selected and further analysed. It was observed that prediction accuracy reduces from Unmanned Aerial Systems (UASs) to satellite platforms, though advances in machine learning techniques could further assist in the generation of better calibration models. There are some challenges concerning atmospheric, radiometric and geometric corrections, vegetation cover, soil moisture and roughness that still need to be addressed. The advantages and disadvantages of each approach are highlighted and future considerations are also discussed at the end.

Remote Sensing Techniques for Soil Organic Carbon Estimation: A Review

Soil salinization management for sustainable development: A review

Beginning with a discussion of drought definitions, this review paper attempts to provide a review of fundamental concepts of drought, classification of droughts, drought indices, and the role of remote sensing and geographic information systems for drought evaluation. Owing to the rise in water demand and looming climate change, recent years have witnessed much focus on global drought scenarios. As a natural hazard, drought is best characterized by multiple climatological and hydrological parameters. An understanding of the relationships between these two sets of parameters is necessary to develop measures for mitigating the impacts of droughts. Droughts are recognized as an environmental disaster and have attracted the attention of environmentalists, ecologists, hydrologists, meteorologists, geologists, and agricultural scientists. Temperatures; high winds; low relative humidity; and timing and characteristics of rains, including distribution of rainy days during crop growing seasons, intensity, and duration of rain, and onset and termination, play a significant role in the occurrence of droughts. In contrast to aridity, which is a permanent feature of climate and is restricted to low rainfall areas, a drought is a temporary aberration. Often, there is confusion between a heat wave and a drought, and the distinction is emphasized between heat wave and drought, noting that a typical time scale associated with a heat wave is on the order of a week, while a drought may persist for months or even years. The combination of a heat wave and a drought has dire socio-economic consequences. Drought risk is a product of a region’s exposure to the natural hazard and its vulnerability to extended periods of water shortage. If nations and regions are to make progress in reducing the serious consequences of drought, they must improve their understanding of the hazard and the factors that influence vulnerability. It is critical for drought-prone regions to better understand their drought climatology (i.e., the probability of drought at different levels of intensity and duration) and establish comprehensive and integrated drought information system that incorporates climate, soil, and water supply factors such as precipitation, temperature, soil moisture, snow pack, reservoir and lake levels, ground water levels, and stream flow. All drought-prone nations should develop national drought policies and preparedness plans that place emphasis on risk management rather than following the traditional approach of crisis management, where the emphasis is on reactive, emergency response measures. Crisis management decreases self-reliance and increases dependence on government and donors.

Drought risk assessment using remote sensing and GIS techniques

Application of near-infrared reflectance for quantitative assessment of soil properties

Smart farming for improving agricultural management

Mapping soil salinity in the East Nile Delta using several methodological approaches of salinity assessment

This study aims to use spatial analyses and a geographic information system (GIS) to assess the environmental sensitivity for desertification in the north Sinai Peninsula, Egypt. Based on the Mediterranean Desertification and Land Use (MEDALUS) approach and the characteristics of the study area, a regional model was developed using GIS. Five main indicators of desertification including soil, climate, erosion, plant cover, and management were considered for estimating the environmental sensitivity to desertification. A spatial analyst extension Arc-GIS 10 software was used for matching the thematic layers and assessing the desertification index, of which the map of environmentally sensitive areas of the north Sinai Peninsula is produced. The obtained data reveals that 65 % of north Sinai is characterized by very severe sensitivity to desertification while the low sensitive one exhibits only 1.2 %. The moderately sensitive area occupies approximately 23 % of the study area. ETM+ and SPOT images are recommended to monitor sensitivity. The MEDALUS model was developed under the Egyptians to assess desertification sensitivity.

E.S. Mohamed

Papers

Drought risk assessment using remote sensing and GIS techniques

Application of near-infrared reflectance for quantitative assessment of soil properties

Smart farming for improving agricultural management

Mapping soil salinity in the East Nile Delta using several methodological approaches of salinity assessment

Spatial assessment of desertification in north Sinai using modified MEDLAUS model