Remote sensing of emergent and submerged wetlands: an overview

To plan for wetland protection and responsible coastal development, scientists and managers need to monitor changes in the coastal zone, as the sea level continues to rise and the coastal population keeps expanding. Advances in sensor design and data analysis techniques are now making remote-sensing systems practical and cost-effective for monitoring natural and human-induced coastal changes. Multispectral and hyperspectral imagers, light detection and ranging (lidar), and radar systems are available for mapping coastal marshes, submerged aquatic vegetation, coral reefs, beach profiles, algal blooms, and concentrations of suspended particles and dissolved substances in coastal waters. Since coastal ecosystems have high spatial complexity and temporal variability, they should be observed with high spatial, spectral, and temporal resolutions. New satellites, carrying sensors with fine spatial (0.4–4 m) or spectral (200 narrow bands) resolution, are now more accurately detecting changes in coastal wetland extent, ecosystem health, biological productivity, and habitat quality. Using airborne lidars, one can produce topographic and bathymetric maps, even in moderately turbid coastal waters. Imaging radars are sensitive to soil moisture and inundation and can detect hydrologic features beneath the vegetation canopy. Combining these techniques and using time-series of images enables scientists to study the health of coastal ecosystems and accurately determine long-term trends and short-term changes.     

Remote sensing and active tectonics of South India

The Indian Peninsula in general and its southern part in particular has been thought to be a stable shield area and hence inert to younger earth movements and seismicities. However, in addition to fast relapsing seismicities, the studies carried out by earlier workers during the past three decades indicate possible pulsatory tectonism, at least since the Jurassics. The present study is a newer attempt to identify, analyse, and spatially amalgamate a large number of anomalies visibly displayed by the tectonic, fluvial, coastal, and hydrological systems in remote sensing and ground based datasets/observations, and to finally paint a fair picture on the active tectonic scenario of South India. The study reveals that the phenomena, viz. extensive soil erosion, reservoir siltation, sediment dump into the ocean, preferential migration of rivers, restricted marine regression, shrinkage of back waters, withdrawal of creeks, fall of groundwater table, etc., indicate two E–W trending ongoing tectonic (Cymatogenic) archings along Mangalore–Chennai in the north and Cochin–Ramanathapuram in the south. Intervening these two arches, a cymatogenic deep along Ponnani–Palghat–Manamelkudi exhibiting phenomena opposite to the above is observed. In addition, the characteristic tectonic, geomorphic, and hydrological anomalies observed in 1B satellite FCC data, as well as in the field, indicate N–S trending extensional, NE–SW sinistral, and NW–SE dextral strike slip faults. These anomalies and the tectonic features deduced thereupon, indicate that the southern part of the Indian Peninsula is tectonically active due to the northerly to north–northeasterly directed compressive force related to post collision tectonics. This active tectonic model visualized for South India gives a further clue that the whole Indian plate is whirling like a worm with alternate E–W arching and deepening, along with block and transform faulting from Cape Comorin in the south to the Himalayas in the north.     

Remote sensing in BOREAS: Lessons learned

The Boreal Ecosystem Atmosphere Study (BOREAS) was a large, multiyear internationally supported study designed to improve our understanding of the boreal forest biome and its interactions with the atmosphere, biosphere, and the carbon cycle in the face of global climate change. In the initial phase of this study (early 1990s), remote sensing played a key role by providing products needed for planning and modeling. During and after the main BOREAS field campaigns (1994 and 1996), innovative remote sensing approaches and analyses expanded our understanding of the boreal forest in four key areas: (1) definition of vegetation structure, (2) land-cover classification, (3) assessment of the carbon balance, and (4) links between surface properties, weather, and climate. In addition to six BOREAS special issues and over 500 journal papers, a principal legacy of BOREAS is its well-documented and publicly available database, which provides a lasting scientific resource and opportunity to further advance our understanding of this critical northern biome.     

Remote sensing terminology: a reply

Abstract

The widespread misuse of the word ‘acronym’ is pointed out.     

Remote sensing terminology: a reply

A point in the Letter by Curran (1983) on remote sensing terminology is expanded and a further point made.     

Remote sensing of canopy light use efficiency in temperate and boreal forests of North America using MODIS imagery

Light use efficiency (LUE) is an important variable characterizing plant eco-physiological functions and refers to the efficiency at which absorbed solar radiation is converted into photosynthates. The estimation of LUE at regional to global scales would be a significant advantage for global carbon cycle research. Traditional methods for canopy level LUE determination require meteorological inputs which cannot be easily obtained by remote sensing. Here we propose a new algorithm that incorporates the enhanced vegetation index (EVI) and a modified form of land surface temperature (T_m) for the estimation of monthly forest LUE based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Results demonstrate that a model based on EVI × T_m parameterized from ten forest sites can provide reasonable estimates of monthly LUE for temperate and boreal forest ecosystems in North America with an R² of 0.51 (p < 0.001) for the overall dataset. The regression coefficients (a, b) of the LUE–EVI × T_m correlation for these ten sites have been found to be closely correlated with the average EVI (EVI_ave, R² = 0.68, p = 0.003) and the minimum land surface temperature (LST_min, R² = 0.81, p = 0.009), providing a possible approach for model calibration. The calibrated model shows comparably good estimates of LUE for another ten independent forest ecosystems with an overall root mean square error (RMSE) of 0.055 g C per mol photosynthetically active radiation. These results are especially important for the evergreen species due to their limited variability in canopy greenness. The usefulness of this new LUE algorithm is further validated for the estimation of gross primary production (GPP) at these sites with an RMSE of 37.6 g C m^? 2 month^? 1 for all observations, which reflects a 28% improvement over the standard MODIS GPP products. These analyses should be helpful in the further development of ecosystem remote sensing methods and improving our understanding of the responses of various ecosystems to climate change.     

Remote sensing in ecological botany

At the XIIth International Botanical Congress, on July 4, 1975, a new direction in scientific methodology was evaluated for the first time within the framework of an International Union of Biological Sciences—remote sensing of vegetation and the environment. Remote sensing is a method of studying the composition, structure, dynamics, and productivity of ecosystems and the state of the biosphere by means of reflectance and emittance characteristics of the earth's surface measureable from aircraft and spacecraft, and the interpretation of such remotely sensed imagery. Remote cartography is conducted with aerial and space images with a scale of from 1: 1000 to 1:30 000 000. Phytomass can be measured by comparing the dependence of the phytocenometric characteristics with the magnitude of the remotely obtained signal. Phenology and dynamics are revealed by means of optical comparison of successive images. Structural ecological investigations can be based on spatial and factoral integration of ecosystems on single, remotely-sensed images. Remote sensors record spatial and temporal variability of the reflective and emissive characteristics of vegetative ground cover. Anthropogeneous effects are recognized by indication of vegetation clearing, fires, ploughing, overgrazing, water and air pollution, and water and wind erosion.     

Landslide mapping with remote sensing: challenges and opportunities

ABSTRACT

Landslide mapping is the primary step for landslide investigation and prevention. At present, both the accuracy and the degree of automation of landslide mapping with remote sensing (LMRS) are still lower than those of general remote sensing classification. In order to improve the performance, previous attempts have been made to develop new features, classifiers, and rules, whereas few studies have investigated the in-depth causes and the corresponding solutions. In this paper, after reviewing the related literature, some of the fundamental difficulties hindering the improvement of LMRS are disclosed and discussed. Firstly, landslides do not have distinguishable spectral, spatial, or temporal characteristics, as they may actually be covered by other land covers. Secondly, the surface features of a landslide can vary greatly, affected by the different geological factors, geomorphological factors, hydrological factors, weather conditions, and other factors. Thirdly, the differences in the surface features are often remarkable and nonnegligible, and thus it is difficult to identify a landslide with only a few simple criteria. Finally, some solutions to the above difficulties are suggested. It is expected that the accuracy and applicability of LMRS could be greatly improved, by exploiting big data, utilizing the deep learning technique, and modelling the surface spatial structure of the landslide.     

Remote sensing used to detect moisture status of pecan orchards grown in a desert environment

Remote-sensing techniques can detect and up-scale leaf-level physiological responses to large areas, and provide significant and reliable information on water use and irrigation management. The objectives of this study were to screen leaf-level physiological changes that occur during the cyclic irrigation of pecan orchards to determine which responses best represent changes in moisture status of plants and link plant physiological changes to remotely sensed surface reflectance data derived from the Landsat Thematic Mapper and Enhanced Thematic Mapper Plus (ETM+). The study was conducted simultaneously on two southern New Mexico mature pecan orchards. For both orchards, plant physiological responses and remotely sensed surface reflectance data were collected from trees that were either well watered or in water deficit. Remotely sensed variables included reflectance in band 1, the ratio between shortwave infrared (SWIR) bands (B5:B7), the normalized difference vegetation index, and SWIR moisture indices. Midday stem water potential (Ψ_smd) was the best performing leaf-level physiological response variable for detecting moisture status in pecans. The B5:B7 ratio positively and significantly correlated with Ψ_smd in five of six irrigation cycles while multiple linear regression weighted with six remotely sensed surface reflectance variables revealed a significant relationship with moisture status in all cycles in both orchards (R² > 0.73). Because changes in the B5:B7 band ratio and multiple regression of spectral variables correlate with the moisture status of pecan orchards, we conclude that remotely sensed data hold promise for detecting the moisture status of pecans.     

Remote sensing of soil salinity: potentials and constraints

Soil salinity caused by natural or human-induced processes is a major environmental hazard. The global extent of primary salt-affected soils is about 955 M ha, while secondary salinization affects some 77 M ha, with 58% of these in irrigated areas. Nearly 20% of all irrigated land is salt-affected, and this proportion tends to increase in spite of considerable efforts dedicated to land reclamation. This requires careful monitoring of the soil salinity status and variation to curb degradation trends, and secure sustainable land use and management. Multitemporal optical and microwave remote sensing can significantly contribute to detecting temporal changes of salt-related surface features. Airborne geophysics and ground-based electromagnetic induction meters, combined with ground data, have shown potential for mapping depth of salinity occurrence. This paper reviews various sensors (e.g. aerial photographs, satellite- and airborne multispectral sensors, microwave sensors, video imagery, airborne geophysics, hyperspectral sensors, and electromagnetic induction meters) and approaches used for remote identification and mapping of salt-affected areas. Constraints on the use of remote sensing data for mapping salt-affected areas are shown related to the spectral behaviour of salt types, spatial distribution of salts on the terrain surface, temporal changes on salinity, interference of vegetation, and spectral confusions with other terrain surfaces.As raw remote sensing data need substantial transformation for proper feature recognition and mapping, techniques such as spectral unmixing, maximum likelihood classification, fuzzy classification, band ratioing, principal components analysis, and correlation equations are discussed. Lastly, the paper presents modelling of temporal and spatial changes of salinity using combined approaches that incorporate different data fusion and data integration techniques.     

Remote sensing and GIS activities in UNESCO

The role of UNESCO is to promote international peace and security through cooperation in the fields of education, science and culture. In view of eradicating illiteracy, overcoming unsustainability of natural resources, confronting environmental problems, safeguarding historical monuments, and preserving natural and cultural heritage, UNESCO develops international research programmes and makes best possible use of new advances in technology, namely remote sensing and GIS, in order to effectively carry out activities in the framework of its programmes. Part one describes remote sensing and GIS use in international programmes such as the Man and the Biosphere (MAB) programme for biosphere reserve development and ecosystem monitoring, management and conservation; the International Hydrological Programme (IHP) for surface and ground water research management; the International Geological Correlation Programme (IGCP) for the creation of a data base on the spectral signatures of rocks and soils; and in several projects concerning ocean investigation and climate observation conducted in the framework of the Intergovernmental Oceanographic Commission (IOC). In part two constraints of using the remote sensing and GIS technology are addressed and remaining difficulties in accessing and exchanging data, training issues and costs are discussed.     

Remote sensing in sea search and rescue

A classified United States Army line scanner (Texas Instruments Model AAS-24) mounted in a Mohawk aircraft was tested for its air-sea search and rescue potential. Within the environmental parameters indicated the instrument proved effective in identifying both small boats and individual swimmers. Positive identification was made during daylight and night sorties when the location of swimmers was known and in daylight trials when their location was unknown.     

Detection of vegetation fires and burnt areas by remote sensing in insular Southeast Asian conditions: current status of knowledge and future challenges

The humid tropical insular Southeast Asian region is one of the most biologically diverse areas in the world. It contains around 70 Gt of carbon stored in peat deposits susceptible to burning when drained and it has significantly higher population density than any other humid tropical region. This region experiences yearly fire activity of anthropogenic origin with widely varying extent and severity. At the same time, there are several geographic, climatic, and social aspects that complicate fire monitoring in the region. In this review article, we analyse the current knowledge and limitations of active fire detection and burnt area mapping in insular Southeast Asia, highlighting the special characteristics of the region that affect all types of remote-sensing-based regional-level fire monitoring. We conclude that the monitoring methods currently employed have serious limitations that directly affect the reliability of results for fire and burnt area monitoring in this region. With the materials and methods presently available, the regional and global effects of fire activity taking place in insular Southeast Asia are in danger of being underestimated. New approaches utilizing higher spatial and temporal resolution remote-sensing data are needed for more detailed quantification of fire activity and subsequently improved estimation of the effects of fires in this region.     

Remote sensing of foliar chemistry

Remotely sensed data are being used to estimate foliar chemical content as a result of our need for the information and our increasing ability to understand and measure foliar spectra. This paper reviews how stepwise multiple regression and deconvolution have been used to extract chemical information from foliar spectra, and concludes that both methods are useful, but neither is ideal. It is recommended that the focus of research be modeling in the long term and experimentation in the short term. Long-term research should increase our understanding of the interaction between radiation and foliar chemistry so that the focus of research can move from leaf model to canopy model to field experiment. Short-term research should aim to design experiments in which remotely sensed data are used to generate unambiguous and accurate estimates of foliar chemical content.     

Remote sensing of coastlines: detection,extraction and monitoring

This paper reviews the current status of the use of remote sensing for the detection, extraction and monitoring of coastlines. The review takes the US system as an example. However, the issues at hand can be applied to any other part of the world. Visual interpretation of airborne remote sensing data is still widely and popularly used for coastal delineation. However, a variety of remote sensing data and techniques are available to detect, extract and monitor the coastline. The developed techniques have reached a level of maturity such that they are applied in operational settings.     

Remote sensing and river migration in Western India

Abstract

The art of remote sensing has opened up many vistas in the study of river migration as satellite photographs, both in their normal and digitally enhanced modes, vividly show the rivers and their migratory signatures. The rivers migrate for various reasons amongst which tectonic movement is one of the main causes. In the present study an attempt has been made to exhibit the paleochannel network of the rivers of Western India and integrate them with lineament fabric, so as to understand the Quaternary tectonics of the region. The study has shown that Western India shows considerable signs of Quaternary tectonics.     

Remote sensing of violent conflict: eyes from above

The use of remote-sensing technology to study violent conflict has increased considerably over the last 5–10 years. This article surveys this growing field to show which conflict-related impacts are and are not currently possible to detect from afar. A brief overview of the principles of remote-sensing technology and sensor characteristics is provided, followed by a review and discussion of the literature, organized by temporal delay in the visible manifestation of the conflict impact from minutes for structural damage to years for changes to land use/land cover. Remote-sensing technology is most valuable in hard-to-reach and/or dangerous conflict zones where field observations are spotty or non-existent. Although good ground reference data are important for verifying the accuracy of observations derived from remote-sensing imagery, it is possible to corroborate or refute suspect reports with appropriate imagery and analysis techniques.