Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data

Gitelson, Anatoly A.; Kogan, Felix; Spivak, L.; Zakarin, E.; Lebed, L.

doi:10.1109/igarss.1996.516293

Cited by 3 publications

(4 citation statements)

References 4 publications

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“…Therefore, the standard data preparation procedure for the 7-day composite time series now includes a correction of VIS and NIR values following Rao and Chen (1995). The post-launch correction considerably improves the stability of NDVI over time, especially for NOAA-9, and almost eliminates the difference between the level of NDVI for the end of NOAA-9 and beginning of NOAA-11 satellite data (Kogan et al 1996). The thermal bands' measurements were converted to brightness temperatures using a look-up table, and a nonlinear correction was applied following Weinreb et al (1990).…”

Section: Satellite and Ground Datamentioning

confidence: 99%

“…A lack of rainfall and its high variability, frequent droughts, and desiccative winds are typical of Kazakhstan's climate, causing a two-three-fold variation in agricultural production. Recently, a cooperative effort (funded by the Agency for International Development of the United States) involving the Institute for Space Research, the National Meteorological Administration (Kazakhstan), the Desert Research Institute (Israel), and NOAA was directed toward development and validation of VCI-derived estimates of drought in Kazakhstan (Gitelson et al 1996).…”

Section: A Asiamentioning

confidence: 99%

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Global Drought Watch from Space

Kogan

1997

Bull. Amer. Meteor. Soc.

832

491

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Drought is the most damaging environmental phenomenon. During 1967-91, droughts affected 50% of the 2.8 billion people who suffered from weather-related disasters. Since droughts cover large areas, it is difficult to monitor them using conventional systems. In recent years the National Oceanic and Atmospheric Administration has designed a new Advanced Very High Resolution Radiometer-(AVHRR) based Vegetation Condition Index (VCI) and Temperature Condition Index (TCI), which have been useful in detecting and monitoring large area, drought-related vegetation stress. The VCI was derived from the Normalized Difference Vegetation Index (NDVI), which is the ratio of the difference between AVHRR-measured near-infrared and visible reflectance to their sum. The TCI was derived from the 10.3-1 \3-jum AVHRR-measured radiances, converted to brightness temperature (BT). Algorithms were developed to reduce the noise and to adjust NDVI and BT for land surface nonhomogeneity. The VCI and TCI are used to determine the water-and temperature-related vegetation stress occuring during drought. This paper provides the principles of these indices, describes data processing, and gives examples of VCI-TCI applications in different ecological environments of the world. The results presented here are the first attempt to use both NDVI and thermal channels on a large area with very diversified ecological resources. The application of VCI and TCI are illustrated and validated by in situ measurements. These indices were also used for assessment of drought impact on regional agricultural production in South America, Africa, Asia, North America, and Europe. For this purpose, the average VCI-TCI values for a given region and for each week of the growing season were calculated and compared with yields of agricultural crops. The results showed a very strong correlation between these indices and yield, particularly during the critical periods of crop growth.

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Section: Satellite and Ground Datamentioning

confidence: 99%

Section: A Asiamentioning

confidence: 99%

Global Drought Watch from Space

Kogan

1997

Bull. Amer. Meteor. Soc.

832

491

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“…In Central Asia, moisture-related drought indices have been widely used rather than temperature-related ones, due to the major issues of water scarcity in the area [17][18][19], where 80% of the land surface has a higher sensitivity to precipitation anomalies [20]. However, temperature is becoming an important parameter in drought assessment for the better estimation of the potential impacts of climate change on dry-land areas.…”

Section: Introductionmentioning

confidence: 99%

Drought Risk Assessment in Cultivated Areas of Central Asia Using MODIS Time-Series Data

Aitekeyeva

Guo

et al. 2020

Water

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Drought is one of the most damaging environmental hazards and a naturally occurring phenomenon in Central Asia that is accompanied by crucial consequences for the agriculture sector. This research aimed at understanding the nature and extent of drought over the cropland regions of Central Asia with the help of spatiotemporal information from the region. We assessed drought occurrence using the vegetation health index (VHI). An algorithm was developed to reduce the noise of heterogeneous land surfaces by adjusting the vegetation index and brightness temperature. The vegetation condition index (VCI) and temperature condition index (TCI) were calculated using Moderate Resolution Imaging Spectroradiometer (MODIS) products for the growing season (April–September) from 2000 to 2015. The intense drought years were identified and a drought map (drought probability occurrence) was generated. The findings of this research indicated regional heterogeneity in the cropland areas having experienced droughts, observed through spatiotemporal variations. Some of the rain-fed and irrigated croplands of Kazakhstan demonstrated a higher vulnerability to annual drought occurrences and climate change impacts, while other cropland regions were found to be more resistant to such changes. The development of policy tools is required to support informed decision-making and planning processes to adapt to the occurrence of droughts. This could be achieved by the timely assessment, monitoring, and evaluation of the spatiotemporal distribution trends and variabilities of drought occurrences in this region. The results from this study focus on the spatiotemporal variations in drought to reveal the bigger picture in order to better understand the regional capacity for sustainable land management and agricultural activities within a changing environment.

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“…Μπορεί να θεωρηθεί ότι ο VCI είναι στενά συνδεδεμένος με την κατάσταση στην οποία βρίσκεται η βλάστηση μιας συγκεκριμένης περιοχής. Αν τα δεδομένα (συνήθως NOAA/AVHRR) καταγράφονται για αρκετά χρόνια, έτσι ώστε να λαμβάνονται υπόψη τα ακραία φαινόμενα κατά τη μεταβολή των περιβαλλοντικών συνθηκών, τότε ο VCI μπορεί να υποδείξει το ενδεχόμενο δυναμικό της βλάστησης ή τη δυναμικότητα -χωρητικότητα (carrying capacity) του οικοσυστήματος (Kogan, 1995a (Kogan, 1995b;Gitelson et al, 1996), του βαμβακιού στην Κίνα (Kogan, 1995b) και του κριθαριού στη Νότια Ρωσία (Kogan, 1995b (Τσίρος, 2006).…”

Section: δείκτης κατάστασης βλάστησηςunclassified

Δορυφορικές Μεθοδολογίες Αγροκλιματικής-Υδροκλιματικής Ζωνοποίησης Για Γεωργική Παραγωγή

Τσίρος¹,

Tsiros²

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Σχήμα 2.1: Παράγοντες που επηρεάζουν την απόδοση των καλλιεργειών (Fageria et al., 1997). Σχήμα 2.2: Γραφική απεικόνιση της αλληλεπίδρασης μεταξύ της θερμοκρασίας και της φωτοσύνθεσης σε C 3 και C 4 φυτά. Η βέλτιστη θερμοκρασία για φωτοσύνθεση είναι περίπου 25˚C στα C 3 φυτά και γύρω στους 35˚C στα C 4 φυτά (Fageria et al., 1997). Σχήμα 2.3: Γενικές καμπύλες της αντίδρασης του AMAX στη θερμοκρασία για διαφορετικές ομάδες καλλιεργειών (Δαναλάτος, 2007). I=φυτά C 3 σε κρύα και εύκρατα κλίματα, ΙΙ= φυτά C 3 σε θερμά κλίματα, ΙΙΙ= φυτά C 4 σε θερμά κλίματα, IV=φυτά C 4 σε κρύα κλίματα.Σχήμα 2.4: Μέγεθος εξατμιζόμενης επιφάνειας και ρυθμός εξάτμισης (Mavi and Tupper, 2004). Σχήμα 2.5: Γενικευμένο πρότυπο της ανάκλασης, απορρόφησης και εκπομπής της ηλιακής ακτινοβολίας σε πράσινο φύλλο (Mavi and Tupper, 2004). Σχήμα 2.6: Γενικευμένο πρότυπο της ανάκλασης, απορρόφησης και εκπομπής του φωτός (Mavi and Tupper, 2004). Σχήμα 3.1: Η επίδραση της θερμοκρασίας στο μήκος της περιόδου από το φύτρωμα έως την ανθοφορία διαφόρων καλλιεργειών. (•) σίκαλη, (○) σιτάρι, (∆) λινάρι, (□) καλαμπόκι, (x) φασόλι (Δαναλάτος, 2007).

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Estimation of seasonal dynamics of pasture and crop productivity in Kazakhstan using NOAA/AVHRR data

Cited by 3 publications

References 4 publications

Global Drought Watch from Space

Global Drought Watch from Space

Drought Risk Assessment in Cultivated Areas of Central Asia Using MODIS Time-Series Data

Δορυφορικές Μεθοδολογίες Αγροκλιματικής-Υδροκλιματικής Ζωνοποίησης Για Γεωργική Παραγωγή

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