SPOT Satellite Imagery Research Articles

TOWARDS HIGH RESOLUTION FEATURE MAPPNG WITH SENTINEL-2 IMAGES

Abstract. High resolution feature mapping from medium resolution imageries gained special attention among remote sensing user community with the launch of Copernicus’ Sentinel-2 mission due to its capability to provide global coverage with relatively high revisit time at no cost. In this paper, we have examined and evaluated the potential of high resolution (2.5m) feature mapping from Sentinel-2 imageries with the aid of artificial intelligence. Generative adversarial network (GAN) is used as single image super resolution (SISR) technology in this study. And SPOT satellite imageries are used as corresponding high-resolution images. From qualitative and quantitative analysis of the experimental results found that spectral quality of the generated images is adequate for remote sensing applications. In conclusion, high resolution feature mapping from Sentinel-2 images found to be feasible to a greater extent for remote sensing applications.

Street Network: Physical and Cultural Transformations on the Morphology of Historical City of Malacca

The deterioration of streets in the historical city of Malacca in Malaysia due to modernization contributes to the streets’ vulnerabilities. This paper purposely analyses the physical transformation of the street networks for the years of 1993-2015, and the cultural influences and impact throughout the establishment of multi-racial cultural society. The methodology for the study is through mapping the street networks of Malacca city by using SPOT satellite imageries of three different years; 1993, 2005, and 2015, and through the street semi-automatic extraction technique to monitor the street pattern of Malacca city. Multiple sensors of SPOT were used, consisting of SPOT-2XS, SPOT 5, and SPOT 6 with 20 m, 5 m, and 1.5 m resolutions in extracting the street objects, while using the IMAGINE OBJECTIVE tools from ERDAS. The finding shows that the street network trend varied from 1993, 2005, and 2015 where the streets achieved 23.8% street expansions in the year 1993 compared to 10.49% in the year 2005. However, the development trend of streets increased to 14.68% in the year 2015. The connection of the physical transformations of the streets with the cultural impact contributed to the sense of place and divided the streets based on socio-economic, cultural and ethnic lines. Finally, it shows that the trend and pattern of street networks were essential in understanding a city’s morphology that has a significant impact on cultural evolution since the establishment of the Chinese community in Malacca.

Distribution and area changes of mangroves with remote sensing technology in Perancak Estuary, Jembrana, Bali

Mangrove vegetation has an important role for its functions and benefits to the coastal area and the society which lives in it. The purpose of this research is to know the distribution and the changes of mangrove vegetation area located in Perancak Estuary area within 10 years, and to know the green-ness level and the environmental parameters of mangrove vegetation; salinity and substrate condition. To observe the distribution and the changes of mangrove vegetation area, supervised classification is used on SPOT satellite imagery in 2007 and 2017. The result shows that the expansion of mangrove vegetation area in Perancak Estuary is 18.7 hectares along with the increasing of the green-ness level. In addition, the environmental parameters which are the salinity and the substrate conditions are also observed, where the average salinity value is 31.54 ppt and the substrate conditions are good (not much waste).

Glacial geomorphology of the Strait of Magellan ice lobe, southernmost Patagonia, South America

ABSTRACT We present a geomorphic map of the landforms created by the Patagonian Ice Sheet during the local Last Glacial Maximum and perhaps prior glaciations in southernmost Patagonia. Building on prior work, the new mapping focuses in unprecedented detail on the right lateral and frontal landforms formed by the Strait of Magellan ice lobe. We produced the map using aerial orthophotography, Sentinel-2 and SPOT satellite imagery, ALOS PALSAR digital elevation model and fieldwork to ground-truth preliminary interpretations. We delineate at least five glacial events defined by a sequence of moraine drifts and associated glaciofluvial features. In contrast to previous studies, we propose the Magellan ice lobe extended ∼65 km farther, to the Primera Angostura peninsula, during the local Last Glacial Maximum. Our study provides a new context to establish a precise glacial chronology of the Magellan ice lobe during the last glacial cycle in the middle-high latitudes of the Southern Hemisphere.

Analysing suitability of arable land within a convertible production forest (HPK)

Potential land resources become one basic information needed in planning agroecological system development. The purpose of this study was to analyse the suitability of arable land in a convertible production forest area (HPK) in Konawe Kepulauan Regency, Southeast Sulawesi Province. Identification of arable land types and determination of agroecological zones was using spatial analysis through SPOT satellite imagery processing and slope map overlays and soil types to determine arable land units. Existing plant species were recorded and adjusted to the direction of land use from the Agricultural Research and Development Agency. From this study, 30 units of fertile land were obtained covering an area of 12,873.69 ha and spread across six zones, namely zone I covering 182.95 ha (1.42%), II covering 3,102.10 ha (24.10%), III covering 3,125.83 ha (24.28%), IV covering 3,594.36 ha (27.92%), V covering 631.85 ha (4.91%) and VI covering 2,236.61 ha (17.37%) with the distribution of plant species in the form of natural forests, annual crop agriculture, seasonal crops, agroforestry crops and food crops. Plants in zones I, II and III in accordance with the direction of land use but Zones IV, V and VI still not suitable.

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.

Boundary Delineation of Agricultural Fields in Multitemporal Satellite Imagery

Agricultural land-use statistics are more informative per-field than per-pixel. Land-use classification requires up-to-date field boundary maps potentially covering large areas containing thousands of farms. This kind of map is usually difficult to obtain. We have developed a new, automated method for deriving closed polygons around fields from time-series satellite imagery. We have been using this method operationally in New Zealand to map whole districts using imagery from several satellite sensors, with little need to vary parameters. Our method looks for boundaries—either step edges or linear features—surrounding regions of low variability throughout the time series. Local standard deviations from all image dates are combined, and the result is convolved with a series of extended directional edge filters. We propose that edge linearity over a long distance is a more important criterion than spectral difference for separating fields, so edge responses are thresholded primarily by length rather than strength. The resulting raster edge map (combined from all directions) is converted to vector (GIS) format and the final polygon topology is built. The method successfully segments parcels containing different crops and pasture, as well as those separated by boundaries such as roads and hedgerows. Here we describe the technique and demonstrate it for an agricultural study site (4000 km2) using SPOT satellite imagery. We show that our result compares favorably with that from existing segmentation methods in terms of both quantitative quality metrics and suitability for land-use classification.

WETLAND CLASSIFICATION FOR BLACK DUCK HABITAT MANAGEMENT USING COMBINED POLARIMETRIC RADARSAT 2 AND SPOT IMAGERY

Abstract. The black duck population has decreased significantly due to loss of its breeding habitat. Wetlands are an important feature that relates to habitat management and requires monitoring. Synthetic Aperture Radar (SAR) systems are helpful to map the wetland as the microwave signals are sensitive to water content and can be used to map surface water extent, saturated soils, and flooded vegetation. In this study, RadarSat 2 Polarimetric data is employed to map surface water and track changes in extent over the years through image thresholding and reviewed different approaches of Polarimetric decompositions for detecting flooded vegetation. Also, object-based analysis associated with beaver activity is conducted with combined multispectral SPOT satellite imagery. Results show SAR data has proven ability to improve mapping open water areas and locate flooded vegetation areas.

Impact of land cover change on aboveground carbon stocks in Afromontane landscape in Kenya

Land cover change takes place in sub-Saharan Africa as forests and shrublands are converted to agricultural lands in order to meet the needs of growing population. Changes in land cover also impact carbon sequestration in vegetation cover with an influence on climate on continental scale. The impact of land cover change on tree aboveground carbon stocks was studied in Taita Hills, Kenya. The land cover change between 1987 and 2011 for four points of time was assessed using SPOT satellite imagery, while the carbon density in various land cover types was assessed with field measurements, allometric biomass functions and airborne laser scanning data. Finally, the mean carbon densities of land cover types were combined with land cover maps resulting in carbon stock values for given land cover types for each point of time studied. Expansion of croplands has been taking place since 1987 and before on the cost of thickets and shrublands, especially on the foothills and lowlands. Due to the land cover changes, the carbon stock of trees was decreasing until 2003, after which there has been an increase. The findings of the research is supported by forest transition model, which emphasizes increase of awareness of forests' role in providing ecosystem services, such as habitats for pollinators, water harvesting and storage at the same time when economic reasons in making land-use choices between cropland and woodland, and governmental legislation supports trees on farms.

Impacts on the Urban Environment: Land Cover Change Trajectories and Landscape Fragmentation in Post-War Western Area, Sierra Leone

An influential underlying driver of human-induced landscape change is civil war and other forms of conflict that cause human displacement. Internally displaced persons (IDPs) increase environmental pressures at their destination locations while reducing them at their origins. This increased pressure presents an environment for increased land cover change (LCC) rates and landscape fragmentation. To test whether this hypothesis is correct, this research sought to understand LCC dynamics in the Western Area of Sierra Leone from 1976 to 2011, a period including pre-conflict, conflict, and post-conflict eras, using Landsat and SPOT satellite imagery. A trajectory analysis of classified images compared LCC trajectories before and during the war (1976–2000) with after the war (2003–2011). Over the 35-year period, the built-up land class rapidly increased, in parallel with an increase in urban and peri-urban agriculture. During the war, urban and peri-urban agriculture became a major livelihood activity for displaced rural residents to make the region food self-sufficient, especially when the war destabilised food production activities. The reluctance of IDPs to return to their rural homes after the war caused an increased demand for land driven by housing needs. Meanwhile, protected forest and other forest declined. A significant finding to emerge from this research is that landscape fragmentation increased in conjunction with declining forest cover while built-up areas aggregated. This has important implications for the region’s flora, fauna, and human populations given that other research has shown that landscape fragmentation affects the landscape’s ability to provide important ecosystem services.

Climate change impact on rainfed agriculture in Aguascalientes, Mexico for the near future (2015-2039)

Los objetivos de la investigación fueron: 1) Evaluar los impactos probables del cambio climático (CC) en la agricultura de secano (AS) en Aguascalientes, México, con base en el modelo HadGEM2-ES para el forzamiento radiativo 8.5 en un futuro cercano, 2015-2039; y 2) Determinar la magnitud de los impactos del CC en la aptitud productiva de la AS a través del análisis de la variabilidad de la precipitación media anual (PMA). La unidad de estudio comprendió el territorio de Aguascalientes, cuyos climas predominantes son semiseco [BS1k w, BS1hw(w)] y templado subhúmedo [C(wO)], y PMA de 526 mm. La evaluación del impacto potencial del CC en la AS de Aguascalientes se basa en el análisis de características edáficas y topográficas en las cuales se practica esta actividad y se complementa con el análisis de la PMA para el futuro cercano, apoyados con imágenes satelitales tipo SPOT. Los resultados indican incrementos probables en la PMA del 20 %, lo cual no necesariamente garantiza un impacto positivo en la productividad del cultivo de maíz, ya que hay factores asociados a las condiciones edáficas, topográficas y de las políticas de uso de la tierra que determinan el éxito del mismo.

Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam.

BackgroundWith more than half of Africa’s population expected to live in urban settlements by 2030, the burden of malaria among urban populations in Africa continues to rise with an increasing number of people at risk of infection. However, malaria intervention across Africa remains focused on rural, highly endemic communities with far fewer strategic policy directions for the control of malaria in rapidly growing African urban settlements. The complex and heterogeneous nature of urban malaria requires a better understanding of the spatial and temporal patterns of urban malaria risk in order to design effective urban malaria control programs. In this study, we use remotely sensed variables and other environmental covariates to examine the predictability of intra-urban variations of malaria infection risk across the rapidly growing city of Dar es Salaam, Tanzania between 2006 and 2014.MethodsHigh resolution SPOT satellite imagery was used to identify urban environmental factors associated malaria prevalence in Dar es Salaam. Supervised classification with a random forest classifier was used to develop high resolution land cover classes that were combined with malaria parasite prevalence data to identify environmental factors that influence localized heterogeneity of malaria transmission and develop a high resolution predictive malaria risk map of Dar es Salaam.ResultsResults indicate that the risk of malaria infection varied across the city. The risk of infection increased away from the city centre with lower parasite prevalence predicted in administrative units in the city centre compared to administrative units in the peri-urban suburbs. The variation in malaria risk within Dar es Salaam was shown to be influenced by varying environmental factors. Higher malaria risks were associated with proximity to dense vegetation, inland water and wet/swampy areas while lower risk of infection was predicted in densely built-up areas.ConclusionsThe predictive maps produced can serve as valuable resources for municipal councils aiming to shrink the extents of malaria across cities, target resources for vector control or intensify mosquito and disease surveillance. The semi-automated modelling process developed can be replicated in other urban areas to identify factors that influence heterogeneity in malaria risk patterns and detect vulnerable zones. There is a definite need to expand research into the unique epidemiology of malaria transmission in urban areas for focal elimination and sustained control agendas.Electronic supplementary materialThe online version of this article (doi:10.1186/s12942-016-0051-y) contains supplementary material, which is available to authorized users.

An integrated approach for the detection of small archaeological sites along palaeochannels: A case study in the Northeast Chaohu area, China

Because of the flourishing vegetation and developed agriculture in eastern China, it is difficult to extract information of small archaeological sites from remote sensing images based only on spectral analysis. This article presents an integrated approach for detecting mound-shaped archaeological sites of the Zhegao region in the northeast Chaohu area. Initial studies of SPOT satellite imagery have shown evidence of a prominent palaeochannel river system, buried under land cover in the western Zhegao region. Digital 1:50000 topographical maps can be highly effective in determining mound-shaped sites and their elevation in this area. These mound-shaped sites include known and unknown small archaeological sites of the Neolithic and Pre-Qin periods. A database of seven known small archaeological sites imported into a GIS environment can be utilized to help understand their relationship with identified palaeochannels. By integrating above multi-source data, three likely archaeological sites were identified from the many mound-shaped sites and tested by field survey. This integrated method strengthens the use of multi-geoinformation technologies in archaeological surveys of subtropical agricultural areas. The results also suggest that there is a close relationship between small archaeological sites and palaeochannels, and other raised mounds adjoining identified palaeochannels should be selected for further exploration.

Preliminary report on the July 10–11, 2015 eruption at Volcán de Colima: Pyroclastic density currents with exceptional runouts and volume

On July 10–11, 2015 an eruption occurred at Colima volcano produced 10.5km long pyroclastic density currents (PDCs) along the Montegrande, and 6.5km long along the San Antonio ravines. The summit dome was destroyed and a new crater excavated and breached to the south. This new breach connects to a narrow channel that descends along Colima's southern flank and was used by a subsequent lava flow. The Montegrande PDCs represent the longest and hottest flow of this type recorded during the past 30years but are still smaller in comparison to the 15-km long PDCs produced during the 1913 Plinian eruption. Data obtained from field reconnaissance, lahar monitoring stations, and satellite imagery suggest that at least six PDCs occurred. The two largest PDCs (H/L 0.2) were able to surmount topographic barriers or bends. Based on field reconnaissance and digital elevation models extracted from SPOT satellite imageries we estimate a minimum volume for the valley-pond and distal fan deposits of 4.5×106m3. After one week, the deposits were still hot with burning trees on the surface and millimeter-sized holes from which fumes were emanating. The juvenile components of the deposits consist of gray dense blocks and vesicular dark-gray blocks and bombs with bread-crust textures and cooling joints. The mineral association of these rocks consists of plagioclase+clinopyroxene+orthopyroxene+FeTi-oxides±olivine and resorbed hornblende in a dark glassy matrix that corresponds to an andesitic composition.

Towards an automated monitoring of human settlements in South Africa using high resolution SPOT satellite imagery

Abstract. Urban areas in sub-Saharan Africa are growing at an unprecedented pace. Much of this growth is taking place in informal settlements. In South Africa more than 10% of the population live in urban informal settlements. South Africa has established a National Informal Settlement Development Programme (NUSP) to respond to these challenges. This programme is designed to support the National Department of Human Settlement (NDHS) in its implementation of the Upgrading Informal Settlements Programme (UISP) with the objective of eventually upgrading all informal settlements in the country. Currently, the NDHS does not have access to an updated national dataset captured at the same scale using source data that can be used to understand the status of informal settlements in the country. This pilot study is developing a fully automated workflow for the wall-to-wall processing of SPOT-5 satellite imagery of South Africa. The workflow includes an automatic image information extraction based on multiscale textural and morphological image features extraction. The advanced image feature compression and optimization together with innovative learning and classification techniques allow a processing of the SPOT-5 images using the Landsat-based National Land Cover (NLC) of South Africa from the year 2000 as low-resolution thematic reference layers as. The workflow was tested on 42 SPOT scenes based on a stratified sampling. The derived building information was validated against a visually interpreted building point data set and produced an accuracy of 97 per cent. Given this positive result, is planned to process the most recent wall-to-wall coverage as well as the archived imagery available since 2007 in the near future.

An ensemble classification approach for improved Land use/cover change detection

Abstract. Change Detection (CD) methods based on post-classification comparison approaches are claimed to provide potentially reliable results. They are considered to be most obvious quantitative method in the analysis of Land Use Land Cover (LULC) changes which provides from - to change information. But, the performance of post-classification comparison approaches highly depends on the accuracy of classification of individual images used for comparison. Hence, we present a classification approach that produce accurate classified results which aids to obtain improved change detection results. Machine learning is a part of broader framework in change detection, where neural networks have drawn much attention. Neural network algorithms adaptively estimate continuous functions from input data without mathematical representation of output dependence on input. A common practice for classification is to use Multi-Layer-Perceptron (MLP) neural network with backpropogation learning algorithm for prediction. To increase the ability of learning and prediction, multiple inputs (spectral, texture, topography, and multi-temporal information) are generally stacked to incorporate diversity of information. On the other hand literatures claims backpropagation algorithm to exhibit weak and unstable learning in use of multiple inputs, while dealing with complex datasets characterized by mixed uncertainty levels. To address the problem of learning complex information, we propose an ensemble classification technique that incorporates multiple inputs for classification unlike traditional stacking of multiple input data. In this paper, we present an Endorsement Theory based ensemble classification that integrates multiple information, in terms of prediction probabilities, to produce final classification results. Three different input datasets are used in this study: spectral, texture and indices, from SPOT-4 multispectral imagery captured on 1998 and 2003. Each SPOT image is classified individually to produce the classified output and used for comparison. A MLP is trained with the input datasets separately using a backpropagation learning algorithm and prediction probabilities are produced for each pixel as evidence against each LU/LC class. An integration rule based on Endorsement Theory is applied to these multiple evidence by considering their individual contribution and the most probable class of a pixel is identified. Integration of the three datasets by the proposed method is found to produce 88.4 % and 84.6 % for individual image. The proposed method improves the potential of using SPOT satellite imagery for change detection.

Mapping wetland characteristics for sustainable development in Harare: The case of Borrowdale West, Highlands, National Sport stadium and Mukuvisi Woodlands wetlands

Wetland ecosystems are under threat from agriculture and urbanisation, affecting water supply and quality in urban areas like the City of Harare. With the need to protect wetlands that remain, the spatial extent of the Highlands, Borrowdale West, Mukuvisi and National Sports wetlands was established. LANDSAT and SPOT Satellite imagery were used to map the spatial extent on the wetlands and to take note of the temporal changes that occurred between 1989 and 2009. Supervised classification was used to classify the images. High resolution Google earth imagery were then downloaded and used as baseline data for mapping the wetlands using the Cowardin wetland classification system 1979 and the Land Capability Classification system for wetness. Maps showing the physical characteristic of the wetlands were then produced. Results indicated that area under wetlands has been shrinking over the years. Using the wetland classification system it was found out that much of the area under wetland should not be used for any other landuse purpose other than wetland protection. However the study found out that urban expansion projects are currently modifying the wetlands. The Highlands wetland has been drained and road construction is currently in progress while a Hotel is under construction on the National sports wetland covering 287 012 m 2 of the wetland. This study provides information on the current physical state of the wetlands, which can be the basis for wetland protection and management by policy makers and managers. Key Words: Wetland, Spatial extent, Physical characteristics, Classification, Landuse, Protection and Management

Coupling a sugarcane crop model with the remotely sensed time series of fIPAR to optimise the yield estimation

The objective of this study was to assess the efficiency of the assimilation of the fraction of intercepted photosynthetically active radiation (fIPAR) data derived from Satellite Pour l’Observation de la Terre SPOT images into the MOSICAS sugarcane crop growth model for estimating the yield at field scale on Reunion Island. Over 3 years, time series of SPOT satellite imagery were used to estimate the daily evolution of NDVI for 60 plots located on two climatically contrasted farms. Ground measurements of the fIPAR were performed on 5 reference fields and used to calibrate a relationship with the corresponding NDVI values. Forced and not forced simulations were run and compared with respect to their ability to predict the final observed yield. Forcing MOSICAS with fIPAR values derived from SPOT images improved the accuracy of the model for the yield estimation (RMSE=12.2 against 14.8tha−1) closer to the 1:1 line. However, underestimations of the yield by the forced model suggest that some of the model parameters were not optimal. The maximal radiation use efficiency parameter (RUEm) was optimised for each field, and an analysis of variance showed the significant effect of the ratoon number of the field, of its cultivar and of the farm where it is planted. Accordingly, the RUEm was recalibrated for each cultivar for the number of ratoons and farms. New RUEm values ranged from 3.09 to 3.77gMJ−1, and new computations were run using the optimised values of RUEm. The results indicate that recalibrating the maximal radiation use efficiency according to the number of ratoons improved the yield estimation accuracy by as much as 10.5tha−1 RMSE. This study highlights the potential of time series of satellite images to enhance the estimation of the yield by a forced ecophysiological model and to obtain better knowledge about the ecophysiological processes that are involved in crop dynamics with the recalibration method.

Spatial distribution analysis of mass movements triggered by the 2005 Kashmir earthquake in the Northeast Himalayas of Pakistan

Distribution of the mass movements triggered by the 2005 Kashmir earthquake was analysed in the vicinity of Jhelum Valley, Neelum Valley, and Muzaffarabad in the Northeast Himalayas of Pakistan. Mass movements were mapped using SPOT satellite imagery and field investigations. Geographic information systems (GIS) were used to analyse the relations of the distribution of these mass movements using various parameters, such as distance from an earthquake source (epicentre and fault), topographic parameters (slope steepness, slope aspect, and elevation) and geological units.The results of the analysis indicate that the mass movement concentration decreases with increased distance from the earthquake epicentre and the reactivated Muzaffarabad Fault. The maximum concentration of mass movements is near the epicentre and a fault. A significant occurrence and concentration of mass movements were evident at slope angles between 31–40°. The preferred orientations of the mass movements were in southerly directions. The concentrations of mass movements differ substantially among various geological units. Mass movements are widely distributed in the Miocene Murree Formation, whereas the concentration of mass movements is higher in the Cambrian Muzaffarabad Formation.The median mass movement concentration inflicted by the epicentre and the Muzaffarabad Fault exhibited no significant differences (KS=0.505; p=0.961). The results of the PCA reveal that the largest variance in mass movement concentration is attributed to the distance from the epicentre and the Muzaffarabad Fault. The findings suggest that the mass movement concentration is primarily dependent on the distance from the earthquake source. In addition, the topographic parameters and geological units played subordinate roles in the distribution of mass movements.

Correlation of meteorological parameters and remotely sensed normalized difference vegetation index (NDVI) with cotton leaf curl virus (CLCV) in Multan

Climate change and weather has a profound effect on the spread of Cotton Leaf Curl Virus (CLCV) which is transmitted by whitefly. Climate change is altering temperature and precipitation patterns, resulting in the shift of some insect/pest from small population to large population thus effecting crops yield. To find out the relationship between the weather conditions, outburst of CLCV and changes in Normalized Difference Vegetation Index (NDVI) values due to the outburst of CLCV, a study was carried out for tehsil Multan. Data was acquired for the months of June, July, August and September for the year 2010. Regression analysis between CLCV and meteorological conditions as well as between CLCV and NDVI was performed. Meteorological parameters included temperature, humidity, precipitation, cloud cover, wind direction, pan evaporation and sunshine hours. NDVI values were calculated from SPOT satellite imagery (1km) using ArcMap10 and WinDisp v5.1. Correlation coefficients obtained in most of the cases were acceptable however the significance F and P-value were higher than their critical value at 95% level of significance. Therefore significant correlation was found only between CLCV and temperature and between CLCV and PAN evaporation during the month of July.