ESTIMATING LEAF AREA INDEX FOR AN ARID REGION USING SPECTRAL DATA

Leaf Area Index (LAI) is one of the important crop parameters that can be used to assess crop conditions or drought severity. Estimating LAI for arid regions presents challenge due to the high spatial variability in precipitation and in crop canopies found in such regions. In this study, spectral reflectance of pearl millet was computed at various wavelengths and at different times during the cropping season, using a spectroradiometer. Three main indices (Normalised Difference Vegetation Index, Ratio Vegetation Index, and Perpendicular Vegetation Index) were derived from the spectral data. These indices were then correlated with the leaf area index in order to identify the index that gave the strongest relationship. A polynomial relationship, with the coefficient of correlation of 0.70, was found between LAI and NDVI indicating that NDVI is a potential index for estimating LAI for arid regions.L\u2019indice de la surface foliaire (ISF) est une d\u2019importants param\ue8tres culturaux pouvant \ueatre utilis\ue9 pour \ue9valuer les conditions des cultures ou la s\ue9v\ue9rit\ue9 de la s\ue8cheresse. L\u2019estimation de ISF en r\ue9gions arides pr\ue9sente une contrainte due \ue0 la variabilit\ue9 spatiale dans la pr\ue9cipitation et la canop\ue9e des cultures dans de telles r\ue9gions. Dans cette \ue9tude, la reflectance spectrale du mil ( Pennisetum glaucum [L.] R. Br.) \ue9tait calcul\ue9e \ue0 des longueurs d\u2019onde vari\ue9es et \ue0 des moments diff\ue9rents durant la saison culturale utilisant un spectroradiom\ue8tre. Trois indices principaux (l\u2019Indice de diff\ue9rence de v\ue9g\ue9tation normalis\ue9e, le Rapport d\u2019indice de v\ue9g\ue9tation, et, l\u2019Indice perpendiculaire de v\ue9g\ue9tation) \ue9taient d\ue9duits des donn\ue9es spectrales. Ces indices \ue9taient ainsi corr\ue9l\ue9s avec l\u2019indice de la surface foliaire afin d\u2019identifier l\u2019indice ayant une plus forte relation. Une relation polynomiale avec le coefficient de corr\ue9lation de 0.70 \ue9tait trouv\ue9e entre ISF et NDVI indiquant que NDVI est un indice potentiel pour l\u2019estimation d\u2019ISF dans des r\ue9gions aride

Impact of local weather variability on irrigation water use in Georgia

Irrigation is often used to offset the impact of rainfall variability on crop yield and to reduce the risk associated with weather variability. However, especially for the state of Georgia, how much water is required and how much water is actually being used for irrigation is largely unknown. The objective of this study was to determine the relationship between farmers' irrigation applications, crop types, and local weather conditions. Farmers' monthly irrigation applications for three major crops in Georgia, i.e., cotton, peanut and maize, were obtained from selected sites of the Agricultural Water Pumping program. Significant relationships between monthly irrigation depth and monthly water deficit were obtained for only two of seven months for cotton, five of seven months for peanut, and only one of six months for maize. Individual differences among farmers on how much water they applied contributed to the lack of correlation between monthly irrigation depth and monthly water deficit. Future efforts should focus on a better understanding of the factors that contribute to the farmer's decisions related to when to irrigate and how much water to apply.Sponsored by: Georgia Environmental Protection Division U.S. Geological Survey, Georgia Water Science Center U.S. Department of Agriculture, Natural Resources Conservation Service Georgia Institute of Technology, Georgia Water Resources Institute The University of Georgia, Water Resources Facult

Detection, Emission Estimation and Risk Prediction of Forest Fires in China Using Satellite Sensors and Simulation Models in the Past Three Decades—An Overview

Forest fires have major impact on ecosystems and greatly impact the amount of greenhouse gases and aerosols in the atmosphere. This paper presents an overview in the forest fire detection, emission estimation, and fire risk prediction in China using satellite imagery, climate data, and various simulation models over the past three decades. Since the 1980s, remotely-sensed data acquired by many satellites, such as NOAA/AVHRR, FY-series, MODIS, CBERS, and ENVISAT, have been widely utilized for detecting forest fire hot spots and burned areas in China. Some developed algorithms have been utilized for detecting the forest fire hot spots at a sub-pixel level. With respect to modeling the forest burning emission, a remote sensing data-driven Net Primary productivity (NPP) estimation model was developed for estimating forest biomass and fuel. In order to improve the forest fire risk modeling in China, real-time meteorological data, such as surface temperature, relative humidity, wind speed and direction, have been used as the model input for improving prediction of forest fire occurrence and its behavior. Shortwave infrared (SWIR) and near infrared (NIR) channels of satellite sensors have been employed for detecting live fuel moisture content (FMC), and the Normalized Difference Water Index (NDWI) was used for evaluating the forest vegetation condition and its moisture status

ESTIMATING LEAF AREA INDEX FOR AN ARID REGION USING SPECTRAL DATA

Leaf Area Index (LAI) is one of the important crop parameters that can be used to assess crop conditions or drought severity. Estimating LAI for arid regions presents challenge due to the high spatial variability in precipitation and in crop canopies found in such regions. In this study, spectral reflectance of pearl millet was computed at various wavelengths and at different times during the cropping season, using a spectroradiometer. Three main indices (Normalised Difference Vegetation Index, Ratio Vegetation Index, and Perpendicular Vegetation Index) were derived from the spectral data. These indices were then correlated with the leaf area index in order to identify the index that gave the strongest relationship. A polynomial relationship, with the coefficient of correlation of 0.70, was found between LAI and NDVI indicating that NDVI is a potential index for estimating LAI for arid regions.L’indice de la surface foliaire (ISF) est une d’importants paramètres culturaux pouvant être utilisé pour évaluer les conditions des cultures ou la sévérité de la sècheresse. L’estimation de ISF en régions arides présente une contrainte due à la variabilité spatiale dans la précipitation et la canopée des cultures dans de telles régions. Dans cette étude, la reflectance spectrale du mil ( Pennisetum glaucum [L.] R. Br.) était calculée à des longueurs d’onde variées et à des moments différents durant la saison culturale utilisant un spectroradiomètre. Trois indices principaux (l’Indice de différence de végétation normalisée, le Rapport d’indice de végétation, et, l’Indice perpendiculaire de végétation) étaient déduits des données spectrales. Ces indices étaient ainsi corrélés avec l’indice de la surface foliaire afin d’identifier l’indice ayant une plus forte relation. Une relation polynomiale avec le coefficient de corrélation de 0.70 était trouvée entre ISF et NDVI indiquant que NDVI est un indice potentiel pour l’estimation d’ISF dans des régions aride

A drought monitoring operational system for China using satellite data: design and evaluation

Droughts occur frequently in China and their real-time monitoring and timely reporting are required for prevention and mitigation. This paper presents a method for developing an operational drought monitoring system for China. The method is based on various components such as Moderate Resolution Imaging Spectroradiometer data access, data processing, indices calculations, drought monitoring and analysis, and information dissemination. The system was tested by monitoring drought conditions in the early spring of 2009 in the Hai Basin of China. Results were compared with the in situ data-based indices. It was found that the system was capable of monitoring spatial variation in vegetation conditions attributed to droughts. The traditional meteorological drought index and yield data were collected to evaluate the system performance. A stronger relationship was found between the vegetation health index and the three-month standard precipitation index for the rainfed cropped areas. The relationship between the drought-area percentage and the winter wheat yield reduction percentage for 16 counties was stronger for the April–May period than for the February–March period. The drought monitoring system could explain about 60% of the variance in the winter wheat yields

Water Use Estimation for Some Major Crops in Georgia Using Geospatial Modeling

Proceedings of the 2003 Georgia Water Resources Conference, held April 23-24, 2003, at the University of Georgia.Agricultural water use estimation can contribute to finding a satisfactory solution of the water dispute among the states of Alabama, Florida, and Georgia. In this paper, the depths of irrigation for cotton, peanut, corn, and soybean are estimated for the Flint, Central, and Coastal water zones of Georgia for 2000, 2001, and 2002. In addition, the volume of irrigation for these crops are estimated for 2000 and 2001. The estimation was based on the spatial interpolation of the data collected under the Agricultural Water Pumping project. The interpolation techniques included the inverse distance weighting, local polynomial, global polynomial, radial basis function, ordinary kriging, and universal kriging. The total volume of irrigation was highest for the Flint zone (578.4 Mm3 ), followed by the Central zone (296.3 Mm3 ) and the Coastal zone (103.0 Mm3 ) for 2000. For 2001, the irrigation volume declined by 41% for the Flint zone, 31% for the Central zone, and 20% for the Coastal zone

Estimating Statewide Irrigation Requirements Using a Crop Simulation Model

Proceedings of the 2003 Georgia Water Resources Conference, held April 23-24, 2003, at the University of Georgia.An understanding of water needs in agriculture is a critical input in resolving the water resource issues that confront the state of Georgia. Unfortunately, how much water is required and how much water is actually being used for irrigation is unknown. The objective of this study was to estimate water demand for irrigation for the entire state of Georgia using a crop simulation model. The irrigation requirements for all the counties where irrigated cotton, corn, peanut and soybean were grown in 2000, 2001 and 2002 were estimated using the Environmental Policy Integrated Climate (EPIC) model. These counties were distributed across seven regions; with three regions, i.e., Flint Basin, Central Coastal Plain and Coastal Zone, representing the major growing areas. The combined irrigation withdrawal in the Flint Basin, Central Coastal Plain and Coastal Zone accounted for about 98% and 99% of the statewide total irrigation withdrawal in 2000 and 2001, respectively, mainly due to large irrigated acreage in those regions. Statewide total irrigation withdrawal was estimated to be 199,125 Mgallons in 2000 and 114,101 Mgallons in 2001. These irrigation requirements will vary from year to year depending on the spatial and temporal distribution of rainfall during the growing season. Total irrigated acreage also had a major impact on irrigation withdrawal. We will implement the model for other crops to determine the total irrigation withdrawals for agriculture in the state of Georgia

Agricultural Water Use Associated with Animal Production Systems in Georgia

Proceedings of the 2003 Georgia Water Resources Conference, held April 23-24, 2003, at the University of Georgia.Agricultural waters use normally centers on the large cross-section of irrigation withdrawals by cropping systems. However, animal production systems are also a significant component of water use in the state of Georgia. These production systems are therefore directly affected by the continuing drought and limited availability of water. Many animal production facilities, such as dairies, poultry houses, processing plants, and related operations use water continuously throughout the year. Some of these facilities could be prime candidates for improvements in water use efficiency and water conservation. The main emphasis of this paper will be to present an overview of water use associated with animal production systems in the state of Georgia