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Spatial-Temporal Patterns of Agricultural Drought in Upper Progo Watershed Based on Remote Sensing and Land Physical Characteristics

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@article{IJASEIT8087,
   author = {Wahyu Widiyatmoko and - Sudibyakto and Emilya Nurjani and Eka Wulan Safriani},
   title = {Spatial-Temporal Patterns of Agricultural Drought in Upper Progo Watershed Based on Remote Sensing and Land Physical Characteristics},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {9},
   number = {2},
   year = {2019},
   pages = {480--488},
   keywords = {agricultural drought; spatial-temporal analysis; spatial modeling.},
   abstract = {

Agricultural drought is alarmed by meteorological drought characterized by lower year-to-year rainfall. Under long period and continuous water deficits, plants may demonstrate stress symptoms and wilt or die. Furthermore, agricultural drought leads to crop failures and threaten the food security of an area. Progo Hulu sub-watershed is a major agricultural area in Temanggung Regency. Spatial-temporal pattern-based information about agricultural drought can be a basis for decision making in drought mitigation. This study aims to analyze spatial and temporal distribution patterns of drought, analyze the physical characteristics of land and their influence on drought pattern, and establish a prediction model of drought distribution patterns based on four physical characteristics of the land. Landsat 8 imagery is used to determine the spatial and temporal patterns of agricultural drought in Upper Progo watershed using an improved Temperature vegetation Dryness Index (iTVDI). Slope, land use, landform, and soil texture are the physical characteristics of land as the variables to determine the most influential factor of drought pattern. They are analyzed using multiple regression analysis techniques. Pixel samples are obtained through purposive sampling method based on land units. The results reveal that the spatial-temporal distribution of agricultural drought occurs rapidly on the slopes and foothills of Sumbing and Sindoro. These areas have the highest average value of the iTVDI index. Agricultural drought extends gradually in line with the number of days without rainfall. Landform is a physical characteristic that most influences the distribution of agricultural drought. The established model by utilizing four variables of physical characteristics generates an average value which almost similar to the iTVDI value produced by remote sensing data. The model can be useful to estimate drought distribution based on the number of days without rainfall.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=8087},    doi = {10.18517/ijaseit.9.2.8087} }

EndNote

%A Widiyatmoko, Wahyu
%A Sudibyakto, -
%A Nurjani, Emilya
%A Safriani, Eka Wulan
%D 2019
%T Spatial-Temporal Patterns of Agricultural Drought in Upper Progo Watershed Based on Remote Sensing and Land Physical Characteristics
%B 2019
%9 agricultural drought; spatial-temporal analysis; spatial modeling.
%! Spatial-Temporal Patterns of Agricultural Drought in Upper Progo Watershed Based on Remote Sensing and Land Physical Characteristics
%K agricultural drought; spatial-temporal analysis; spatial modeling.
%X 

Agricultural drought is alarmed by meteorological drought characterized by lower year-to-year rainfall. Under long period and continuous water deficits, plants may demonstrate stress symptoms and wilt or die. Furthermore, agricultural drought leads to crop failures and threaten the food security of an area. Progo Hulu sub-watershed is a major agricultural area in Temanggung Regency. Spatial-temporal pattern-based information about agricultural drought can be a basis for decision making in drought mitigation. This study aims to analyze spatial and temporal distribution patterns of drought, analyze the physical characteristics of land and their influence on drought pattern, and establish a prediction model of drought distribution patterns based on four physical characteristics of the land. Landsat 8 imagery is used to determine the spatial and temporal patterns of agricultural drought in Upper Progo watershed using an improved Temperature vegetation Dryness Index (iTVDI). Slope, land use, landform, and soil texture are the physical characteristics of land as the variables to determine the most influential factor of drought pattern. They are analyzed using multiple regression analysis techniques. Pixel samples are obtained through purposive sampling method based on land units. The results reveal that the spatial-temporal distribution of agricultural drought occurs rapidly on the slopes and foothills of Sumbing and Sindoro. These areas have the highest average value of the iTVDI index. Agricultural drought extends gradually in line with the number of days without rainfall. Landform is a physical characteristic that most influences the distribution of agricultural drought. The established model by utilizing four variables of physical characteristics generates an average value which almost similar to the iTVDI value produced by remote sensing data. The model can be useful to estimate drought distribution based on the number of days without rainfall.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=8087 %R doi:10.18517/ijaseit.9.2.8087 %J International Journal on Advanced Science, Engineering and Information Technology %V 9 %N 2 %@ 2088-5334

IEEE

Wahyu Widiyatmoko,- Sudibyakto,Emilya Nurjani and Eka Wulan Safriani,"Spatial-Temporal Patterns of Agricultural Drought in Upper Progo Watershed Based on Remote Sensing and Land Physical Characteristics," International Journal on Advanced Science, Engineering and Information Technology, vol. 9, no. 2, pp. 480-488, 2019. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.9.2.8087.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Widiyatmoko, Wahyu
AU  - Sudibyakto, -
AU  - Nurjani, Emilya
AU  - Safriani, Eka Wulan
PY  - 2019
TI  - Spatial-Temporal Patterns of Agricultural Drought in Upper Progo Watershed Based on Remote Sensing and Land Physical Characteristics
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 9 (2019) No. 2
Y2  - 2019
SP  - 480
EP  - 488
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - agricultural drought; spatial-temporal analysis; spatial modeling.
N2  - 

Agricultural drought is alarmed by meteorological drought characterized by lower year-to-year rainfall. Under long period and continuous water deficits, plants may demonstrate stress symptoms and wilt or die. Furthermore, agricultural drought leads to crop failures and threaten the food security of an area. Progo Hulu sub-watershed is a major agricultural area in Temanggung Regency. Spatial-temporal pattern-based information about agricultural drought can be a basis for decision making in drought mitigation. This study aims to analyze spatial and temporal distribution patterns of drought, analyze the physical characteristics of land and their influence on drought pattern, and establish a prediction model of drought distribution patterns based on four physical characteristics of the land. Landsat 8 imagery is used to determine the spatial and temporal patterns of agricultural drought in Upper Progo watershed using an improved Temperature vegetation Dryness Index (iTVDI). Slope, land use, landform, and soil texture are the physical characteristics of land as the variables to determine the most influential factor of drought pattern. They are analyzed using multiple regression analysis techniques. Pixel samples are obtained through purposive sampling method based on land units. The results reveal that the spatial-temporal distribution of agricultural drought occurs rapidly on the slopes and foothills of Sumbing and Sindoro. These areas have the highest average value of the iTVDI index. Agricultural drought extends gradually in line with the number of days without rainfall. Landform is a physical characteristic that most influences the distribution of agricultural drought. The established model by utilizing four variables of physical characteristics generates an average value which almost similar to the iTVDI value produced by remote sensing data. The model can be useful to estimate drought distribution based on the number of days without rainfall.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=8087 DO - 10.18517/ijaseit.9.2.8087

RefWorks

RT Journal Article
ID 8087
A1 Widiyatmoko, Wahyu
A1 Sudibyakto, -
A1 Nurjani, Emilya
A1 Safriani, Eka Wulan
T1 Spatial-Temporal Patterns of Agricultural Drought in Upper Progo Watershed Based on Remote Sensing and Land Physical Characteristics
JF International Journal on Advanced Science, Engineering and Information Technology
VO 9
IS 2
YR 2019
SP 480
OP 488
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 agricultural drought; spatial-temporal analysis; spatial modeling.
AB 

Agricultural drought is alarmed by meteorological drought characterized by lower year-to-year rainfall. Under long period and continuous water deficits, plants may demonstrate stress symptoms and wilt or die. Furthermore, agricultural drought leads to crop failures and threaten the food security of an area. Progo Hulu sub-watershed is a major agricultural area in Temanggung Regency. Spatial-temporal pattern-based information about agricultural drought can be a basis for decision making in drought mitigation. This study aims to analyze spatial and temporal distribution patterns of drought, analyze the physical characteristics of land and their influence on drought pattern, and establish a prediction model of drought distribution patterns based on four physical characteristics of the land. Landsat 8 imagery is used to determine the spatial and temporal patterns of agricultural drought in Upper Progo watershed using an improved Temperature vegetation Dryness Index (iTVDI). Slope, land use, landform, and soil texture are the physical characteristics of land as the variables to determine the most influential factor of drought pattern. They are analyzed using multiple regression analysis techniques. Pixel samples are obtained through purposive sampling method based on land units. The results reveal that the spatial-temporal distribution of agricultural drought occurs rapidly on the slopes and foothills of Sumbing and Sindoro. These areas have the highest average value of the iTVDI index. Agricultural drought extends gradually in line with the number of days without rainfall. Landform is a physical characteristic that most influences the distribution of agricultural drought. The established model by utilizing four variables of physical characteristics generates an average value which almost similar to the iTVDI value produced by remote sensing data. The model can be useful to estimate drought distribution based on the number of days without rainfall.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=8087 DO - 10.18517/ijaseit.9.2.8087