Weed Control Decision Support System Based on Precision Agriculture Approach

Herbicides have been widely used for weed control in modern agriculture. However the use of herbicides is potentialy introducing negative impact to the environment due to excessive use of herbicides. Based on precision agriculture principles, unique and precise treatment of herbicide supply for a particular area for crop production must be performed. The objective of this research is to develop a decision support system (DSS) for schedulling of weed spraying and for selecting the proper nozzle size of the sprayers that introduce minimum negative impact to the environment. The main set of data required for our proposed system includes the set of 10 years weather data series acquired from remote sensing (NOAA and TRMM) and a set of vegetation index from MODIS EVI. The weather data set is utilized to determine the planting time period of paddy crop and to determine the proper size of the sprayers for weed spraying. Our DSS prototype has been implemented and tested with real data set in Jonggol district, West Java, Indonesia. The implementation, testing results, and future enhancement of our system are discussed in this paper

GIS-based suitability analysis on hybrid renewal energy site allocation using integrated MODIS and ASTER Satellite imageries in Peninsular Malaysia

© 2018 Proceedings - 39th Asian Conference on Remote Sensing: Remote Sensing Enabling Prosperity, ACRS 2018 This study attempts to find the most suitable places to establish hybrid renewable energy sites (e.g. biomass and solar energy) in Malaysia. We used space borne satellite-derived solar irradiance estimation which is useful and accurate approach for solar resource calculation. To do so, MODIS Terra and Aqua satellite were used to extract values of Aerosol Optical Depth (AOD) at 550 nm. Subsequently, other topographic contribution factors were derived from ASTER satellite imagery. MODIS satellite imagery was classified by support vector machine to extract land use/land cover. Additionally, sixteen different metrological stations were utilized to calibrate the solar irradiances achieved from MODIS satellite and provide daily wind data over the entire Peninsular Malaysia. Finally, simple additive weighting method was implemented in geographical information system (GIS) platform to develop the hybrid RE suitability model. MODIS solar radiation result showed a high correlation with field observation. The result of hybrid renewable energy suitability analysis revealed that coastal areas of Hulu Terengganu, have high potential for allocating sites. This country scale research can be used as a guidance/preliminary assessment to narrow down the scope of new potential hybrid RE in regional scale

Geospatial multi-criteria analysis for identifying high priority clean energy investment opportunities: A case study on land-use conflict in Bangladesh

Bangladesh is a globally important emerging economy with rapidly increasing energy demand. The Bangladeshi government's primary capacity expansion plan is to install 13.3 GW of new coal by 2021, including the 1.3 GW Rampal coal power plant to be developed in the Sundarbans. Inadequate geospatial and economic information on clean energy investment opportunities are often a significant barrier for policy makers. Our study helps fill this gap by applying a new method to assess energy investment opportunities, with focus on understanding land-use conflicts, particularly important in this context as Bangladesh is constrained on land for agriculture, human settlements, and ecological preservation. By extending a geospatial multi-criteria analysis model (MapRE) we analyze the cost of various renewable energy generation technologies based on resource availability and key siting criteria such as proximity to transmission and exclusion from steep slopes, dense settlements or ecologically sensitive areas. We find there is more utility-scale solar potential than previously estimated, which can be developed at lower costs than coal power and with minimal cropland tradeoff. We also find significant potential for decentralized roof-top solar in commercial and residential areas. Even with a conservative land use program that reserves maximum land for agriculture and human settlement, there is more renewable energy capacity than needed to support Bangladeshi growth. This study provides critical and timely information for capacity expansion planning in South Asia and demonstrates the use of geospatial models to support decision-making in data-limited contexts

Assessment of high speed internet for remote sensing data acquisition and exchange in Colombia and Latin America

New remote sensing platforms and data programs have dramatically increased the availability of satellite image data for analysis of climate, agriculture, environment and society. Particularly important new sensor systems include the USA’s MODIS system, Brazil and China’s CBER platform, and India’s IRS satellite. These and other systems have created considerable benefits to the international community of remote sensing analysts. Today, we have more data with greater options regarding spatial, radiometric and temporal resolution. While having these greater options is a positive development, substantial problems remain in acquiring and managing large data volumes. Data providers and consumers must support significant costs in copying remote sensing data to tapes and disks. Internet transfer of satellite imagery is only possible on broadband networks. Even then, download times can be considerable. Downloads may be interrupted if the Internet connections are unstable. How can we improve the acquisition of large volumes of remote sensing data for environmental analysis? What alternatives are available to remote sensing researchers to acquire near-real time satellite imagery for research use? This paper assesses the potential of high-speed Internet as a medium for transferring large satellite imagery data sets between the United States and Colombia, between Colombia and other Latin American countries and within Colombia. Academic and research networks have led developments in high-speed Internet. Many countries throughout the world are installing the infrastructure needed to develop these networks. In the United States this system is referred to as Internet 2. Latin American countries are developing a system called RedCLARA (Cooperación Latinoamerican

Land and cryosphere products from Suomi NPP VIIRS: overview and status

[1] The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument was launched in October 2011 as part of the Suomi National Polar-Orbiting Partnership (S-NPP). The VIIRS instrument was designed to improve upon the capabilities of the operational Advanced Very High Resolution Radiometer and provide observation continuity with NASA's Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS). Since the VIIRS first-light images were received in November 2011, NASA- and NOAA-funded scientists have been working to evaluate the instrument performance and generate land and cryosphere products to meet the needs of the NOAA operational users and the NASA science community. NOAA's focus has been on refining a suite of operational products known as Environmental Data Records (EDRs), which were developed according to project specifications under the National Polar-Orbiting Environmental Satellite System. The NASA S-NPP Science Team has focused on evaluating the EDRs for science use, developing and testing additional products to meet science data needs, and providing MODIS data product continuity. This paper presents to-date findings of the NASA Science Team's evaluation of the VIIRS land and cryosphere EDRs, specifically Surface Reflectance, Land Surface Temperature, Surface Albedo, Vegetation Indices, Surface Type, Active Fires, Snow Cover, Ice Surface Temperature, and Sea Ice Characterization. The study concludes that, for MODIS data product continuity and earth system science, an enhanced suite of land and cryosphere products and associated data system capabilities are needed beyond the EDRs currently available from the VIIRS

Using GIS to Predict Corn Yields in Colombia

Crop yield prediction can play an important role in developing the agriculture sector in Colombia. Remote sensing and GIS have proven to be an effective mechanism for this purpose in developed economies. This project created a proof-of-concept application for the Colombian Ministry of Agriculture and other related governmental institutions. The project used existing methodologies including the classification of satellite imagery, interpolation of climate data into continuous surfaces, the extraction of Normalized Difference Vegetation Index, and the computation of multiple linear regressions. ESRI ArcGIS provided the interface, software, tools and functions to build the application, and to integrate and automate the application‟s functionalities. Cloud coverage in the imagery and the lack of specialized data affected the accuracy of the crop yields estimates. Nevertheless, the application predicts corn yields with an estimated accuracy of 71% when cloud coverage is minimal. The application can use both Landsat and Spot preprocessed images, and in less than six minutes yield predictions for areas inside Cordoba, a major corn producing state in Colombia

Hydrologic and Agricultural Earth Observations and Modeling for the Water-Food Nexus

In a globalizing and rapidly-developing world, reliable, sustainable access to water and food are inextricably linked to each other and basic human rights. Achieving security and sustainability in both requires recognition of these linkages, as well as continued innovations in both science and policy. We present case studies of how Earth observations are being used in applications at the nexus of water and food security: crop monitoring in support of G20 global market assessments, water stress early warning for USAID, soil moisture monitoring for USDA's Foreign Agricultural Service, and identifying food security vulnerabilities for climate change assessments for the UN and the UK international development agency. These case studies demonstrate that Earth observations are essential for providing the data and scalability to monitor relevant indicators across space and time, as well as understanding agriculture, the hydrological cycle, and the water-food nexus. The described projects follow the guidelines for co-developing useable knowledge for sustainable development policy. We show how working closely with stakeholders is essential for transforming NASA Earth observations into accurate, timely, and relevant information for water-food nexus decision support. We conclude with recommendations for continued efforts in using Earth observations for addressing the water-food nexus and the need to incorporate the role of energy for improved food and water security assessment