SPOT Satellite Research Articles

Landcover classification of satellite images based on an adaptive interval fuzzy c-means algorithm coupled with spatial information

ABSTRACTLandcover classifications have large uncertainty related to the heterogeneity of similar objects and complex spatial correlations in satellite images, making it difficult to obtain ideal classification results using traditional classification methods. Therefore, to address the uncertainty in landcover classifications based on remotely sensed information, we propose a novel fuzzy c-means algorithm, which integrates adaptive interval-valued modelling and spatial information. It dynamically adjusts the interval width according to the fuzzy degree of the target membership without pre-setting any parameters, controls the fuzziness of the target, and mines the inherent distribution of the data. Furthermore, reliability-based spatial correlation modelling is used to describe the spatial relationship of the target and to improve both robustness and accuracy of the algorithm. Experimental data consisting of SPOT5 (10-m spatial resolution) or Thematic Mapper (30-m spatial resolution) satellite data for three case study areas in China are used to test this algorithm. Compared with other state-of-the-art fuzzy classification methods, our algorithm markedly improved the ground-object separability. Moreover, it balanced improvement of pixel separability and suppression of heterogeneity of intra-class objects, producing more compact landcover areas and clearer boundaries between classes.

Assessment of the health impact of paper mulberry (Broussonetia papyrifera L.), an invasive plant species in Islamabad, Pakistan.

This study focuses on the risk of pollen allergy due to paper mulberry (Broussonetia papyrifera L.), an Asian invasive plant species now common in large parts of the world. Pollen plays a key role in the pathogenesis of respiratory allergic diseases, particularly rhinitis and asthma, and Islamabad, a major metropolitan city, is severely affected by allergy owing to B. papyrifera pollen. Due to its seasonality and other relationships with climatic variables, we used remote sensing to monitor the trend of pollen count. We also mapped the localisation of patients affected by pollen allergy using geographic information systems. The maximum likelihood algorithm was applied to SPOT-5 satellite imagery for land use/land cover classification. Temporal analysis of remotely sensed data revealed an increasing trend of paper mulberry density towards the southern and south-western part of Islamabad. Although not evident during rainfall, a clear positive correlation was found between patient count and pollen count. Field survey data and hotspot spatial analysis of allergy patients revealed that residents of Shakerperiyan and Lok Virsa areas (Sectors H-8, I-8, I-9, G-8, G-7 and G-6 in Islamabad) had more pronounced symptoms compared to residents of other sectors. The methodology adopted used in this study can be used to map the distribution of similar invasive species in other parts of the country.

Effect of Temperature and Precipitation on the Vegetation Dynamics of High and Moderate Altitude Natural Forests in India

In the present study, the high-altitude vegetation dynamics of natural forest cover were analyzed to find the effect of local hydrology for about 10 years. Vegetation dynamics in four different topographical and climatic conditions in India were studied using normalized difference vegetation index (NDVI) data from vegetation sensor of SPOT satellite, and daily temperature and precipitation data from Asian Precipitation–Highly Resolved Observational Data Integration Towards Evaluation project. The main objective was to understand how and to what extent the natural vegetation reciprocates in various climatic conditions. First, the vegetation data was denoised by using empirical mode decomposition technique. The relation between the vegetation growth and hydrological parameters was studied to find the anomalies. Then, the wavelet analysis of the hydrological data was carried out to find the frequency and extent of the anomalies. Finally, nonparametric Mann–Kendall trend analysis and Sen’s slope analysis were applied to find the trend of the vegetation, temperature, and precipitation dynamics. Results indicate that the growth of the vegetation starts when the average temperature is 10 °C or higher. Beyond that the increase in temperature may have a negligible effect on growth of vegetation. The vegetation also shows positive change in monthly NDVI with the increase in precipitation depending forest type and local climate. However, with excessive rainfall, a declining trend in vegetation growth was observed. The NDVI data show positive trend in all four sites. In northern region, the temperature showed positive trend, while precipitation had negative trend. In eastern and western regions, the temperature had negative trend and precipitation had positive trend.

Analysis of shallow water benthic using of SPOT-6 imagery data on Miang Besar Island, Kutai Timur, Indonesia

Potential observation of coastal waters habitat by an extensive coverage difficult reached by in-situ observation methods, so that using image data is expected to study of data in a short time and broad scope. SPOT-6 satellite multispectral imagery as imagery data was used in this study to interpret habitat conditions spatially. Research was conducted on Miang Besar Island, East Kutai by imagery data processing and field survey. Field surveys in shallow waters to observe the appearance of coral objects, seagrass, and mangroves. Imagery data processing stages by radiometric and geometric correction and transformation of lyzenga algorithm by supervised classification methods. The classification results in 3 community schemes namely; coral, seagrass and mangrove on coastal of Miang Besar island showed a presentation of mangrove communities distribution area 29.000 m2 and percentage cover 54% by Rhizopora apiculata, Seagrass community distribution area 8,900 m2 and percentage cover 76% by Enhalus acorides, and coral community distribution area 5,800 m2 and percentage cover 62% by Hard coral.

Geospatial analysis of land use driving force in coal mining area: case study in Ningdong, China

Geospatial techniques such as remote sensing and Geographic Information System are very important for studying the dynamic process of land use. To analyze the land use change and assess the driving force, SPOT satellite images of 2005, 2010, 2015 and 2018 were used. Classification of land use was applied using Normalized Difference Vegetation Index and Maximum Likelihood Technique in ENVI 5.3. Transition images and matrix were applied using Arcgis10.5 with the Excel PivotTable function. To determine the driving forces of land use change in the study area, Quantitative and Qualitative analysis were applied. Data were compared with statistical analysis using Principal Component Analysis (PCA). Results showed that, the images of the study area were categorized into vegetation (arable land, garden, woodland, grassland, water and agriculture), construction (industrial and transportation) and unutilized land (salt marsh, sandy land, bare land and gully erosion land). From 2005 to 2018, constriction land use greatly increased from 100.41 km2 (2.88%) and 305.13 km2 (8.76%), respectively. Vegetation was decreased from 3190 km2 (91.55%) 3028 km2 (86.91%) in 2005 and 2018, respectively. Results of the comprehensive index of land use degree, dynamic degree, quantitative and qualitative analysis show major changes in land use of the area that caused by human activities especially new developments during the period of the study. The results showed that the Ningdong base in 2005–2018 has been in the stage of sustainable development, mainly in the conversion of grassland, forest land and cultivated land to construction land. High values of rate of change in land use related to the development and new construction and building area. This development might be as a result of anthropogenic activities through urban growth coupled with its potential impacts on urban climate. The principal component analysis shows that human activities drive the change of land use pattern in Ningdong, mainly including the policy of closing the grazing ban, industrialization and scale, population growth and urbanization. Results can provide effective data for the future ecological environment protection and sustainable development of Ningdong Energy Base. Remote sensing is a good technique for assessing the actual sequence in the development of any area that may be caused by human activities.

Remote Sensing for Detecting Changes of Land Use in Taipei City, Taiwan

This study combined statistical analysis and remote sensing techniques to explore the environmental effect of land use and land cover changes in Taipei City, Taiwan. Together with SPOT satellite images from multiple periods (1993, 2003, and 2014), unsupervised Iterative Self-Organizing Data Analysis techniques were used to classify images into three categories: water, vegetation (green area), and non-planting (buildings) areas. An accuracy assessment was conducted to analyze the changes in each administrative region and to explore the differences in the green cover ratios of the various administrative regions through the spatial distribution characteristics of satellite images. We found that if the area of green cover must be increased, the need for green coverage and distribution can be quantified through geospatial analysis to identify preferred sites. In addition to increasing the proportion of green coverage in the city, this approach can effectively mitigate changes in the ambient temperature. The overall accuracy and kappa values of this study were more than 90% and 0.8, respectively, indicating that the image classification results had favorable reliability.

Dual-Frequency Reflectarray Cell to Provide Opposite Phase Shift in Dual Circular Polarization With Application in Multibeam Satellite Antennas

A new reflectarray cell is proposed to simultaneously provide opposite phase shifts between orthogonal circular polarizations at two frequencies (19.7 and 29.5 GHz) by applying a variable rotation technique independently at each frequency. The reflectarray cell, which consists of two dielectric layers with two levels of printed elements (dipoles and arcs), has been characterized for both circular and linear polarizations at each frequency. Apart from the implementation of the variable rotation technique at each frequency, the reflectarray cell provides an additional phase adjustment at the higher frequency, which can be used to shape the beam. This concept applied to multiple spot satellites in Ka-band will allow to produce two adjacent beams per feed in orthogonal circular polarizations at transmission and reception frequency bands.

Space use of Pacific harbor seals (Phoca vitulina richardii) from two haulout locations along the Oregon coast.

BackgroundThere are approximately 10,000–12,000 Pacific harbor seals (Phoca vitulina richardii) inhabiting the Oregon coast, and unlike other species of pinnipeds in this region, are reliably present year-round. Despite this, and drastic rebounds in population since the enactment of the Marine Mammal Protection Act, limited data is available for the present period regarding their space use at sea, and within estuarine, riverine, or bay areas within the state.ObjectiveTo examine site-based differences in space use for 24 adult Pacific harbor seals captured and outfitted with satellite transmitters at two predominant haulout sites on the Oregon Coast, USA.DesignWe captured 24 adult harbor seals from two haulout sites on the Central Oregon coast between September 2014–16 and fitted them with external Wildlife Computers SPOT5 satellite transmitters to track movement. Using state-space modeled locations derived from satellite telemetry data, we evaluated spatial behavior of these animals using a correlated random walk model via R package crawl. Kernel density estimation was subsequently used to calculate home range and core area for each animal. Percent use of open ocean habitat versus use of estuaries, rivers and bays was quantified, as was an initial examination of presence within five newly-established marine reserves in Oregon. Examination of haulout site-related differences in spatial behavior were examined for seals captured in Netarts and Alsea Bays, Oregon and haul out behavior related to time of day, season, and tidal level was also investigated.ResultsThe average individual home range for seals was 364.47 ± 382.87 km2 with seals captured in Alsea bay demonstrating a significantly higher home range area than those captured in Netarts Bay. Alsea bay seals also tended to range farther from shore than Netarts Bay animals. The average calculated core area for seals encompassed on average 29.41 ± 29.23 km2 per animal, however the home range of one animal was so small, core area could not be calculated. Use of marine reserves was limited for animals in this study, representing less than 2% of locations with a majority occurring in Cape Perpetua Marine Reserve and North Marine Protected Area. Seals were more likely to haul out during low tides and periods of low light (dusk, night and dawn), and hauling out behavior increased in winter months.SignificanceThese findings demonstrate the first major documentation of space use of harbor seals in the state for nearly three decades, and lends itself to future comparison and formation of mechanistically-based hypotheses for behavior of a common marine mammal in the highly productive northern California Current System.

A Preferential Interval-Valued Fuzzy C-Means Algorithm for Remotely Sensed Imagery Classification

Remotely sensed imagery classification have a large amount of uncertainty related to the intraclass heterogeneity and the interclass ambiguity of objects. Fuzzy set theory can address the uncertainty effectively, while interval-valued model can improve the separability of samples. Therefore, we propose a novel interval-valued fuzzy c-means algorithm, which integrates the interval-valued model and preferential adaptive method. It preferentially adjusts the interval width according to MSE (mean-square-error) and boundary factor for determining the optimal set of features for the data. In this paper, it is proved that the method can make the intraclass MSE and boundary factor always proportional to the separability of objects, so that it can dynamically adjust the interval-valued separability by controlling the interval width. Experimental data consisting of SPOT5 (10-m spatial resolution) satellite data for three case study areas in China are used to test this algorithm. Compared with other state-of-the-art fuzzy classification methods, our algorithm demonstrates the markedly improved overall accuracy and Kappa coefficients.

Multi-Beam Circular Polarized Reflectarray on Parabolic Reflector by Variable Rotation Technique

Multi-beams antennas are currently being used for direct broadcast satellite, personal communication satellite, military communication satellite, and high-speed internet applications. In this work, a circularly polarized (CP) multi-spot beam satellite parabolic reflectarray antenna is designed to provide six spot beams at 19.7 GHz. For this purpose, an easy technique to compute the required phase shifts to produce two focused beams in specular directions for a CP parabolic reflectarray is proposed. These required phase shifts are added to the reflected fields by the variable rotation of the reflectarray elements printed on the surface of a parabolic antenna which are fed by a dual-CP feed-horn. For this purpose, a reflectarray cell made of a conductive cross embedded in a grounded multilayered substrate is optimized to produce very linear phase-shift and low cross-polarization level. To demonstrate the multibeam capacity, a 1.8-meter offset parabolic reflectarray made of the optimized reflectarray element was designed to generate six focused beams in dual-CP with three dual-CP feed-horns. The six main spots fulfill the typical multi spot satellite requirement with angular separation less than 0.56°, 0.4 dB loss in the gain, and cross-polarization level below 35 dB with respect to the maximum of radiation.

Research on Visual Interpretation and Spatial Distribution Pattern of the Erosion Gully in Luoyugou Watershed of China

There are criss-cross Ravines and gullies in the Loess Plateau, where the erosion gullies grows better. The loess material, which is loose and has the vertical jointing, is easy to suffer from the erosion; the types of erosion in this area mainly include gravitational erosion and the trench erosion. There are typical gulling erosion in Luoyugou watershed of Tianshui northern suburb, located in the interactive region of Longxi Loess plateau hill-gully area and the Longnan mountainous area. Under the support of the SPOT satellite photos in 2008 and field survey, the paper establishes the visual interpretation features of erosion gully, extracting the information of erosion gully, and uses the landscape pattern analytical method, studying the spatial distribution pattern of the erosion gully in the watershed. Finally, the paper draws the following conclusions: 1) The shapes of erosion gullies are strip or arborization, and in the black-white image, the stable erosion gullies appear deep dark color, active erosion gullies present the bright color, and half-active erosion gullies are the shallow dark color; while in color synthesis image, the color of stable erosion gullies mixes garnet, and other erosion gullies are bright green. 2) There are more erosion gullies in the study area where human activities occur frequently, such as the both sides of terraced field, the side of road and the river marshland, the both sides of terraced field have. 3) The erosion gullies in the study watershed are primarily stable ones, whose area accounts for 51.3% of the total erosion gullies, and half-active ones accounts for 18.3%. This phenomenon indicates the progress in the control of the erosion gullies in this basin. 4) From the upstream to the downstream in the research basin, the erosion gully's average shape index has the tendency to reduce gradually, illustrating that the more getting nearly to the downstream, the more the slope of erosion gully to be gentler. The data results match well with the actual terrain feature.

CHALLENGING THE INVISIBILITY OF MOBILE CULTURES REMOTE SENSING, ENVIRONMENT AND ARCHAEOLOGY IN THE NEAR EAST

Abstract. Remote sensing has provided a modern wider perspective to approach the earth with its various environments and impact of humans by prospecting previously unknown frontiers of human life. The traces of mobile groups are archaeologically often more difficult to detect than those of the sedentary ones, but new approaches and methods have changed and enhanced the ways to extract archaeological information of hunter-gatherers and pastoral nomads. Remote sensing, for example, provides alternative views from above and better visibility in a larger scale, especially with high resolution solutions, than on the ground to trace sites. Mobile people have become more visible in archaeology, and therefore their importance in the development of human cultures has received more focus and understanding. This paper will focus on the use of remote sensing in the archaeological study of mobile cultures and their environments in the Near East. Various examples of techniques and site types will be discussed, and the suitability of applications will be considered based on the studies by Finnish and Finnish-Swedish projects in the Near East. We will provide examples of applications and emphasize the importance of empirical approaches in studying archaeological evidence by remote sensing. GPS coordinate points have served as the basis of our field survey and mapping. From the image-based data we shall deal with aerial photographs, CORONA satellite photographs, Landsat, SPOT, QuickBird and GeoEye satellite images. From the range-based data we shall discuss X-SAR Shuttle Mission 2000 and ASTER-DEM data, but LiDAR and geophysical devices will only be briefly considered.

Two Efficient Hybrid Methods for Enhancing Pan-Sharpening of Multi-spectral Images Transmitted from Satellite to Ground Stations

Pan-sharpening is one of the most important tasks performed on satellite images as it enhances spectral and spatial information of the images. Empirical mode decomposition (EMD) is one of the powerful methods for pan-sharpening. It first decomposes the image into a set of intrinsic mode functions and a residual component. These panchromatic and multi-spectral components are then fused to create an enhanced pan-sharpened image. This paper presents two efficient hybrid methods to enhance pan-sharpening of multi-spectral images. The new proposals combine the EMD with the two pan-sharpening methods: high-pass filtering and discrete wavelet transform to maximize the pan-sharpened image quality. The two methods are evaluated using satellite images of Cairo and Suez Canal region, Egypt, captured by Spot-4 and Landsat-8 satellites, respectively. The results imply that the proposed hybrid methods provide better qualitative and quantitative results compared to the individual and the common pan-sharpening methods.

Phenotyping of Plant Biomass and Performance Traits Using Remote Sensing Techniques in Pea (Pisum sativum, L.).

Field pea cultivars are constantly improved through breeding programs to enhance biotic and abiotic stress tolerance and increase seed yield potential. In pea breeding, the Above Ground Biomass (AGBM) is assessed due to its influence on seed yield, canopy closure, and weed suppression. It is also the primary yield component for peas used as a cover crop and/or grazing. Measuring AGBM is destructive and labor-intensive process. Sensor-based phenotyping of such traits can greatly enhance crop breeding efficiency. In this research, high resolution RGB and multispectral images acquired with unmanned aerial systems were used to assess phenotypes in spring and winter pea breeding plots. The Green Red Vegetation Index (GRVI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Red Edge Index (NDRE), plot volume, canopy height, and canopy coverage were extracted from RGB and multispectral information at five imaging times (between 365 to 1948 accumulated degree days/ADD after 1 May) in four winter field pea experiments and at three imaging times (between 1231 to 1648 ADD) in one spring field pea experiment. The image features were compared to ground-truth data including AGBM, lodging, leaf type, days to 50% flowering, days to physiological maturity, number of the first reproductive node, and seed yield. In two of the winter pea experiments, a strong correlation between image features and seed yield was observed at 1268 ADD (flowering). An increase in correlation between image features with the phenological traits such as days to 50% flowering and days to physiological maturity was observed at about 1725 ADD in these winter pea experiments. In the spring pea experiment, the plot volume estimated from images was highly correlated with ground truth canopy height (r = 0.83) at 1231 ADD. In two other winter pea experiments and the spring pea experiment, the GRVI and NDVI features were significantly correlated with AGBM at flowering. When selected image features were used to develop a least absolute shrinkage and selection operator model for AGBM estimation, the correlation coefficient between the actual and predicted AGBM was 0.60 and 0.84 in the winter and spring pea experiments, respectively. A SPOT-6 satellite image (1.5 m resolution) was also evaluated for its applicability to assess biomass and seed yield. The image features extracted from satellite imagery showed significant correlation with seed yield in two winter field pea experiments, however, the trend was not consistent. In summary, the study supports the potential of using unmanned aerial system-based imaging techniques to estimate biomass and crop performance in pea breeding programs.

CAMBIOS DE VEGETACIÓN Y USO DE SUELO EN LA CUENCA RÍO BRAVO-SAN JUAN, COAHUILA (1993 A 2008)


 
 
 Los estudios de cambios de uso de suelo y vegetación sirven de apoyo a los tomadores de decisiones para proponer mejores programas y políticas de manejo y conservación de los recursos naturales. El presente trabajo tuvo el objetivo de identificar los cambios de uso del suelo y vegetación de ocho categorías en el periodo de 1993 a 2008. Se emplearon las cartas de Uso de Suelo y Vegetación Serie II de INEGI y la actualización de Serie III al 2008 mediante imágenes de satélite SPOT. En estos quince años se reconoce un crecimiento de áreas urbanas y agrícolas de 3.8% y 0.2%, respectivamente, a expensas de las zonas de pastizal y matorral, con tasas de cambio negativas de 1.2% para las primeras y 0.1% para las segundas. De la superficie total de 1, 007,837 ha que cubre toda la cuenca: 1.9% (19,537 ha) presentaron cambio de uso de suelo y vegetación, 14,307 ha (1.4% de la cuenca) fueron intercambios entre categorías y 0.5% (5,230 ha) a cambios netos. La relación pérdida/ganancia indica mayor reducción en el pastizal y más ganancia en cuerpos de agua. Los índices de permanencia a ganar son más altos en cuerpos de agua y zona urbana, y con respecto a pérdidas son de pastizal y áreas desprovistas de vegetación. Se concluye que la metodología de estimación de la tasa de cambios, evaluación multitemporal, estimación de cambios (pérdidas, ganancias e intercambios) e índices de persistencia permite analizar de forma detallada las modificaciones de uso de suelo y vegetación de la cuenca bajo estudio.
 
 

Reconstructing Taiwan\u2019s land cover changes between 1904 and 2015 from historical maps and satellite images

A new reconstruction of changes in Taiwan’s land cover and estimated uncertainty between 1904 and 2015 is presented. The reconstruction is made by integrating geographical information from historical maps and SPOT satellite images, to obtain spatially explicit land cover maps with a resolution of 500 × 500 m and distinguishes six land cover classes: forests, grasslands, agricultural land, inland water, built-up land, and bare soil. The temporal resolution is unbalanced being derived from four historical maps describing the land cover between 1904 and 1994 and five mosaic satellite images describing the land cover between 1995 and 2015. The uncertainty of the historical maps is quantified to show the aggregation error whereas the uncertainty of the satellite images is quantified as classification error. Since 1904, Taiwan, as a developing country, has gone through a not unusual sequence of population growth and subsequent urbanization, a decoupling of the demand for agricultural land from population growth, and a transition from shrinking in forest area to forest expansion. This new land cover reconstruction is expected to contribute to future revisions of global land cover reconstructions as well as to studies of (gross) land cover changes, the carbon budget, regional climate, urban heat islands, and air and water pollution at the national and sub-national level.

Spatial analysis of landslide susceptibility using failure rate approach in the Hindu Kush region, Pakistan

This paper analyses and applies a spatio-statistical failure rate (SSFR) technique for landslide susceptibility zonation in the Hindu Kush region, Pakistan. The study area (Shahpur valley) is located in the eastern Hindu Kush mountain system. In Shahpur valley, land sliding is a recurrent and costly extreme event. Geologically, this region constitutes the youngest mountain systems and almost every year landslide-induced losses are reported. The frequency and intensity of landslide events is expected to further increase in future due to rapid population growth over the fragile slopes, infrastructural development and deforestation. In order to achieve objectives of the study, data were obtained from both primary and secondary sources. In Shahpur valley, an inventory of the past 300 landslide events of various sizes has been identified and marked on a SPOT satellite image of 2.5 m resolution. In order to identify the influence of landslide triggering factors, such as geology, tectonic structures, land use, slope angle, slope aspect, roads and streams, a univariate SSFR technique has been tested and applied for calculating the susceptibility score in each class of the selected parameters. Based on factor maps and cumulative score, the landslide susceptibility zones have been developed and validated appearing to be significantly reflecting the pattern of the past landslide events.

An innovative use of orthophotos – possibilities to assess plant productivity from colour infrared aerial orthophotos

AbstractStudies of ecological processes should focus on a relevant spatial scale, as crude spatial resolution will fail to detect small scale variation which is of potentially critical importance. Remote sensing methods based on multispectral satellite images are used to assess primary productivity and aerial photos to map vegetation structure. Both methods are based on the principle that photosynthetically active vegetation has a characteristic spectral signature. Yet they are applied differently due to technical differences. Satellite images are suitable for calculations of vegetation indices, for example Normalized Difference Vegetation Index (NDVI). Colour infrared aerial photography was developed for visual interpretation and never regarded for calculation of indices since the spectrum recorded and post processing differ from satellite images. With digital cameras and improved techniques for generating colour infrared orthophotos, the implications of these differences are uncertain and should be explored. We tested if plant productivity can be assessed using colour infrared aerial orthophotos (0.5 m resolution) by applying the standard NDVI equation. With 112 vegetation samples as ground truth, we evaluated an index that we denote rel‐NDVIortho in two areas of the Fennoscandian mountain tundra. We compared the results with conventional SPOT5 satellite‐based NDVI (10 m resolution). rel‐NDVIortho was related to plant productivity (Northern area: P = <0.001, R2 = 0.73; Southern area: P = <0.001, R2 = 0.39), performed similar to SPOT5 satellite NDVI (Northern area: P = <0.001, R2 = 0.76; Southern area: P = <0.001, R2 = 0.40) and the two methods were highly correlated (cor = 0.95 and cor = 0.84). Despite different plant composition, the results were consistent between areas. Our results suggest that vegetation indices based on colour infrared aerial orthophotos can be a valuable tool in the remote sensing toolbox, offering a high‐spatial resolution proxy for plant productivity with less signal degradation due to atmospheric interference and clouds, compared to satellite images. Further research should aim to investigate if the method is applicable to other ecosystems.

Spatio-Temporal Assessment of Vegetation Resource Dynamics in Nigeria from SPOT Satellite Imageries

Vegetation resources in Nigeria are of vital importance for the sustainable development of the country. However, this essential resource is in danger due to the effect of anthropogenic and climate induced impacts. Currently desert encroachment which cuts across the Sahel is affecting most of the states in the northern part of the country particularly the eleven states considered by the Federal Ministry of Environment in Nigeria as the frontline states. Several studies on the Nigerian environment have shown that there are serious threats to the general environment particularly vegetation. Due to population growth and the need for housing as well as the expansion of the over-utilised farmlands across these states, places considered as reserved areas across the country are being exploited to the detriment of the vegetal resources particularly the forest and rangeland areas. This study utilized Idrisi TerrSet (version 18) raster-based remote sensing and GIS software to analyse seventy two (72) dekadal Normalised Vegetation Index (NDVI) imageries from SPOT satellite covering Nigeria in order to assess the anthropogenic and likely climatic impacts on the vegetal resources using the forward t-mode Principal Component Analysis (PCA) with standardised principal components. Results indicated that Component 1 which explains about 69% of the 72 time-series NDVI imageries shows typical vegetation cover over the study area within the time period under study. While component two indicated a cyclic trend differentiating the ENSO events of 1999 and 2009; component three indicated positive anomaly pattern of vegetation NDVI mostly within Sokoto, Kebbi, Kano, Jigawa and the northern parts of Bauchi, Yobe and Borno states. However, Component four imagery indicated a likely link to the 2009 flood that affected Kainji dam and rivers Niger and Benue. For a better result, the integration of socio-economic and high spatial resolution data into an assessment of this kind in future studies is encouraged.

Integrating Landscape Metrics and Hydrologic Modeling to Assess the Impact of Natural Disturbances on Ecohydrological Processes in the Chenyulan Watershed, Taiwan.

The Chenyulan watershed, located in the central mountain area of Taiwan, has been suffering from earthquakes, typhoons, and heavy rainfalls in recent decades. These sequential natural disturbances have a cumulative impact on the watershed, leading to more fragile and fragmented land cover and loss of capacity of soil water conservation. In this study, the Soil and Water Assessment Tool (SWAT) and a landscape metrics tool (FRAGSTATS) were used to assess the direct impact (e.g., by annual rainfall) and indirect impact (e.g., by landscape configuration and composition) of natural disturbances on the ecohydrological processes of the Chenyulan watershed. Six SPOT satellite images from 2008 to 2013 were analyzed by using the nearest feature line embedding (NFLE) approach and reclassified into six land cover types: forest, cultivated land, grassland, river, landslide, and built-up. Forest was found to have the largest patch size, indicating that it is more resilient to disturbances, while agricultural land tended to expand from the river side toward the hill. Two land cover change scenarios were compared in the SWAT model. The results showed that there was no significant difference in simulated streamflow during 2004–2015 and sediment loading during 2004–2009; however, the model performed better for sediment loading during 2010–2015 with dynamic land cover change (coefficient of determination (R2) = 0.66, Nash-Sutcliffe efficiency coefficient (NSE) = 0.62, percent bias (PBIAS) = 10.5%, root mean square error observation standard deviation ratio (RSR) = 0.62) than with constant land cover (R2 = 0.61, NSE = 0.54, PBIAS = −17.3%, RSR = 0.68), indicating that long-term land cover change should be considered in hydrologic modeling. Changes in landslides during 2008–2013 were found to significantly affect ecohydrological processes, especially after 2011. In general, annual precipitation plays a dominant role, and landscape composition had by far the strongest influence on water yield and sediment yield compared to landscape configuration. The results can be useful for understanding the effects of land cover change on ecohydrological processes in the Chenyulan watershed and the potential impact of ecohydrological changes on the environment and public health.