Ramesh Sivanpillai

Improvements in mapping water bodies using ASTER data

Abstract Coalbed Natural Gas extraction usually results in the production of excess, or product, water, necessitating a strategy for disposal and minimizing landscape and habitat impacts. In the Powder River Basin in Wyoming, product water is either discharged into ephemeral streams or retention/detention ponds. Monitoring these water bodies is important for environmental, habitat, and human health perspectives. This study assessed the benefits of using higher spatial resolution ASTER image, in contrast to more commonly used moderate-resolution Landsat imagery, for detecting smaller water bodies in the Powder River Basin. ASTER and Landsat Thematic Mapper (TM) images were acquired concomitantly and classified following similar methods to identify water bodies for three color classes and a range of sizes. Results showed that the ASTER image had significantly higher accuracies for detecting clear and green colored water bodies, but did not demonstrate significant improvement for detecting turbid water bodies. ASTER also showed significant improvements in detecting small-scale water bodies. However this improved performance was somewhat offset due to the misclassification of other landscape elements as water in the ASTER image. Overall when compared to Landsat TM image, ASTER image more accurately detected more water bodies, especially those with a relatively small surface area, with the two images producing similar results at large scales. The application of ASTER is therefore appropriate for monitoring and evaluation of water bodies in the Powder River Basin and elsewhere.

Estimating regional forest cover in East Texas using Advanced Very High Resolution Radiometer (AVHRR) data

This study tested the degree to which single date, near-nadir AVHRR image could provide forest cover estimates comparable to the phase I estimates obtained from the traditional photo-based techniques of the Forest Inventory and Analysis (FIA) program. FIA program is part of the United States Department of Agriculture-Forest Service (USFS). A six-county region in east Texas was selected for this study. Manual identification of ground control points (GCPs) was necessary for geo-referencing this image with higher precision. Through digital image classification techniques forest classes were separated from other non-forest classes in the study area. Classified AVHRR imagery was compared to two verification datasets: photo-center points and the USFS FIA plots. The overall accuracy values obtained were 67 and 71%, respectively. Analyses of the error matrices indicated that the AVHRR image correctly classified more forested areas than non-forested areas; however, most of the errors could be attributed to certain land cover and land use classes. Several pastures with tree cover, which were field-identified as non-forest, were misclassified as forest in the AVHRR image using the image classification system developed in this study. Recently harvested and young pine forests were misclassified as non-forest in the imagery. County-level forest cover estimates obtained from the AVHRR imagery were within the 95% confidence interval of the corresponding estimates from traditional photo-based methods. These results indicate that AVHRR imagery could be used to estimate county-level forest cover; however, the precision associated with these estimates was lower than that obtained through traditional photo-based techniques.

Can early season Landsat images improve locust habitat monitoring in the Amudarya River Delta of Uzbekistan

Abstract Reed (Phragmites australis) stands of the Amudarya River delta south of the Aral Sea in Uzbekistan serve as permanent breeding areas of the Asian migratory locust (Locusta migratoria migratoria). Locust swarms threaten agricultural fields adjacent to the delta. Every year, specialists from the Uzbekistan Plant Protection Service attempt to survey this vast delta to assess growth of reed which provides a habitat for locust nymphal infestations. Inferences regarding locust distribution are drawn and recommendations for chemical treatments made, based on very limited samples. This often results in blanketing wetland areas with broad-spectrum insecticides, thus harming nontarget fauna. In this study, early season Landsat data, coinciding with the locust survey planning stage, were used to generate a map of potential locust habitat. Using iterative image classification and reference data, a reed distribution map was generated with an overall accuracy of 74% (kappa agreement = 0.686). Landsat data were able to correctly identify 87% of the reed beds, but had some difficulty separating other vegetation when it was mixed with reeds. Minimizing these errors would improve the overall accuracy; however, this does not diminish the utility of this tool for locust habitat monitoring. Incorporation of remotely sensed data into current survey practices could provide precise information about the spatial distribution of reeds. Plant protection specialists could then use this to optimize planning and execution of antilocust treatments, reducing the negative environmental impact of these.

Glacier Impacts on Summer Streamflow in the Wind River Range, Wyoming

AbstractThe Wind River Range (WRR) of Wyoming is host to approximately 63 glaciers. Extensive research has been conducted using remote imagery to estimate the recent area and volume changes of these glaciers with the goal of estimating the potential effects of these changes on watershed streamflow. Results show that the glaciers were mostly in recession since 1966, the beginning of the study period. The current research was performed to supplement results from the remote imagery analyses. In this paper, streamflows from glaciated and nonglaciated watersheds in the WRR for the period 1967–1992 were analyzed. The difference in July-August-September (JAS) watershed flow magnitude for the 26-year period between glaciated (Green River and Bull Lake Creek) and nonglaciated (East Fork River and Wind River) watersheds ranged between 8 and 23%. As expected, the effects of glaciers on local streamflows during JAS were shown to be much greater than that of ice melt alone. The influence of glaciers accounted for 23–5...

Locust Habitat Monitoring and Risk Assessment Using Remote Sensing and GIS Technologies

Locust outbreaks occur on all continents except Antarctica and can affect the livelihoods of one in 10 people on Earth. To prevent economic and environmental losses, locust breeding areas should be periodically monitored, and an early detection-early response strategy should be in place. Traditional, ground survey methods are inefficient to adequately address the large spatial scale of the locust problem. Remote Sensing and the associated geospatial technologies can provide timely data to assess the risk of impending locust outbreaks. This information could be used for targeted preventive management actions in the locust breeding areas. Remotely sensed data are used for monitoring habitats of certain species such as the Desert, Migratory and Australian Plague locusts. However, the vast potential of this technology remains untapped for other locusts. This chapter provides a review of remote sensing and GIS concepts, types of data collected by various remote sensing satellites, and applications of geospatial tools for locust habitat monitoring and risk assessment.

Can late summer Landsat data be used for locating Asian migratory locust, Locusta migratoria migratoria , oviposition sites in the Amudarya River delta, Uzbekistan?

Existing survey methods for assessing the Asian migratory locust, Locusta migratoria migratoria L. (Orthoptera: Acrididae), infestation risk in the Amudarya River delta, Uzbekistan, are largely constrained by economic resources and site accessibility. The surveys are restricted to a few easily accessible areas, which leads to a misinterpretation of the threat of locust infestation. This often results in indiscriminate blanket treatments of vast areas of wetlands with broad‐spectrum insecticides, which may adversely impact non‐target fauna and flora. In order to minimize the bias during surveys, one approach would be to allocate the sampling locations based on the distribution of the primary food and shelter plant of the locusts, the common reed, Phragmites australis (Cav.) Trin. ex Steud (Poaceae). In this study, we evaluated the utility of satellite‐based remotely sensed data (Landsat TM) acquired in August 2006 to characterize reed distribution in the delta and identify potential locust oviposition sites. The overall accuracy of the Landsat data to map land cover classes in the delta was 84%. The Landsat TM data identified 90% of the reeds, but it was less useful in identifying areas where other vegetations (shrubs and grasses) were mixed with reeds. During the following summer field survey in June 2007, we identified 37 sites that were infested with early‐instar locusts. The low migration capacity of young nymphs in dense reed vegetation allowed us to presume that these sites were used for oviposition in the previous summer. Twenty‐eight (74%) of these 37 sites had reeds in the previous year. Results from these studies demonstrate that reed distribution maps derived from satellite data could be used for targeting locust egg‐pod survey locations, in order to minimize sampling bias while predicting locust infestation risks for the following season.

Relating AEROCam-derived NDVI to apparent soil electrical conductivity (ECa) for corn fields in Wyoming, USA

High-spatial-resolution aerial images are necessary to capture variations in crop growth in small fields. The objective of this study was to analyse the relationship between the normalized difference vegetation index (NDVI), derived from Airborne Environmental Research and Observation Camera (AEROCam; 1 m colour infrared) images, and the apparent soil electrical conductivity (ECa) values measured in furrow- and sprinkler-irrigated fields planted with corn (Zea mays L.) in Lingle, Wyoming. NDVI, calculated using 2005, 2006 and 2007 AEROCam images, and ECa were selected, as both variables are used as a measure of potential crop yield. NDVI values exhibited statistically significant exponential relationships with the ECa values for both fields. For the furrow-irrigated field, the adjusted R 2 values ranged between 0.66 and 0.79, and for the sprinkler-irrigated field the adjusted R 2 values ranged between 0.64 and 0.91. Results obtained in this study indicate that AEROCam images can be used for monitoring crop growth in small fields and can provide valuable insights about crop growth patterns when ECa measurements are not available.

WyomingView: No-Cost Remotely Sensed Data for Geographic Education

Abstract Learning enhanced by visual examples and remotely sensed imagery is a valuable classroom resource for teaching students geographic concepts in a meaningful context. Barriers to the use of imagery include difficulty finding appropriate imagery and the cost of moderate resolution satellite imagery. A program in Wyoming called WyomingView and analogous programs in other states are providing no-cost, preprocessed satellite imagery delivered over the Internet that can help teachers better communicate geospatial knowledge to their students.

Near real-time high-resolution airborne camera, AEROCam, for precision agriculture

Precision agriculture often relies on high-resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require high-resolution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration between several departments at the University of North Dakota, including the Upper Midwest Aerospace Consortium (UMAC), the School of Engineering and Mines, and flight operations at the John D. Odegard School of Aerospace Sciences. AEROCam consists of a Redlake MS4100 area-scan multi-spectral digital camera that features a 1920 × 1080 CCD array (7.4-μm detector) with 8-bit quantization. When operated at ∼2 km above ground level, multispectral images with four bands in the visible and near infrared have a ground sample distance of 1 m with a horizontal extent of just over 1.6 km. Depending on the applications, flying at different altitudes can adjust the spatial resolution from 0.25 to 2 m. Rigorous spectral and radiometric calibrations allow AEROCam to be used in a variety of applications, qualitative and quantitative. Equipped with an inertial measurement unit (IMU) system, the images acquired can be geo-referenced automatically and delivered to end users near real time through our Digital Northern Great Plains system (DNGP). The images are also available to zone mapping application for precision farming (ZoneMAP), an online decision support tool for creating management zones from remote sensing imagery and data from other sources. Operational since 2004, AEROCam has flown over 250 sorties and delivered over 150,000 images to the users in the Northern Great Plains region, resulting in numerous applications in precision agriculture and resource management.

Future Landsat Data Needs at the Local and State Levels: An AmericaView Perspective

Abstract Earth observation imagery collected by the series of Landsat satellites constitutes the longest and most consistent collection of moderate spatial resolution remotely sensed data. Feedback from the Landsat user community has played an important role in assessing its utility and making improvements to future Landsat missions. The United States Geological Survey ( usgs ) and the National Aeronautical and Space Administration ( nasa ) continue to solicit input from user communities. This paper describes the outcome of soliciting input from experts associated with AmericaView ( av ), a non-profit organization aimed at promoting remote sensing applications in the us . The av community identified the importance of rigorously calibrated Landsat data for lulc applications at the state level and made several recommendations for future Landsat missions. Recommendations suggested by the community of av experts provide extremely valuable insights to usgs and nasa to further their discussions about the design and operation of future Landsat missions.