TY - GEN
T1 - Study of Dry Climate During Extreme El-Nino Occurrence for Plantation Commodities in Nangapanda, East Nusa Tenggara
AU - Putri, Nadya Paramitha
AU - Saiya, Halvina Grasela
AU - Buditama, Gilang
AU - Yola, Lin
N1 - Funding Information:
Acknowledgements This publication were supported by DRPM (Directorate of Research and Community Service) Universitas Indonesia through PUTI Research Grant with contract number NKB-1271/UN2.RST/HKP.05.00/2020. We want to send our gratitude to the people of Nangapanda. Furthermore, our big thanks to Sanca Pamungkas for helping us to collect data in Nangapanda. Moreover, our gratitude to the Center for Human Resources and Environmental Research (PPSML), that facilitates us to conduct an initial survey through cooperation funds with contract numbers 358G/UN2.F4.D2.2/LT-KEP.SPK/X/2019. An assistance was also provided by the DIVERLING (Biodiversity for Environmental Sustainability) Research Cluster, School of Environmental Science, Universitas Indonesia. This paper’s map can also be done with the help from the Geospatial Laboratory (“Laboratorium Geospasial SIL”) at the School of Environmental Sciences, through using the Map Info Pro license software, ArcGIS ESRI license, and ENVI.
Funding Information:
This publication were supported by DRPM (Directorate of Research and Community Service) Universitas Indonesia through PUTI Research Grant with contract number NKB-1271/UN2.RST/HKP.05.00/2020. We want to send our gratitude to the people of Nangapanda. Furthermore, our big thanks to Sanca Pamungkas for helping us to collect data in Nangapanda. Moreover, our gratitude to the Center for Human Resources and Environmental Research (PPSML), that facilitates us to conduct an initial survey through cooperation funds with contract numbers 358G/UN2.F4.D2.2/LT-KEP.SPK/X/2019. An assistance was also provided by the DIVERLING (Biodiversity for Environmental Sustainability) Research Cluster, School of Environmental Science, Universitas Indonesia. This paper?s map can also be done with the help from the Geospatial Laboratory (?Laboratorium Geospasial SIL?) at the School of Environmental Sciences, through using the Map Info Pro license software, ArcGIS ESRI license, and ENVI.
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2022
Y1 - 2022
N2 - El Nino is an anomaly in sea surface temperature in the Pacific Ocean, resulting in dry conditions and reduced rainfall in Indonesia. This anomaly can cause many things, one of which is a drought that affects plants’ growth. As a region that depends on agriculture, agriculture productivity in Nangapanda can be threatened by the dry condition derived by El Nino events. This research aims to detect the spatial and temporal of dry areas and analyze its relationship with plantation commodities productivity in Nangapanda. Landsat 5 TM and Landsat 8 OLI imagery data at the year 2009, 2015, and 2019 were used for analyzing the Normalization of Differences Vegetation Index (NDVI) and Tasseled Cap Transformation (TCT). Overlay of the NDVI and TCT will generate dry areas divided into moderate, high, and very high drought classes. Dry areas during 2019 are 2942.46 ha or 15% of the total area of Nangapanda Subdistrict. Mostly, drought areas are located in the agricultural area and shrubs area. The increasing dry area can cause a decrease in the productivity of plantation commodities in Nangapanda.
AB - El Nino is an anomaly in sea surface temperature in the Pacific Ocean, resulting in dry conditions and reduced rainfall in Indonesia. This anomaly can cause many things, one of which is a drought that affects plants’ growth. As a region that depends on agriculture, agriculture productivity in Nangapanda can be threatened by the dry condition derived by El Nino events. This research aims to detect the spatial and temporal of dry areas and analyze its relationship with plantation commodities productivity in Nangapanda. Landsat 5 TM and Landsat 8 OLI imagery data at the year 2009, 2015, and 2019 were used for analyzing the Normalization of Differences Vegetation Index (NDVI) and Tasseled Cap Transformation (TCT). Overlay of the NDVI and TCT will generate dry areas divided into moderate, high, and very high drought classes. Dry areas during 2019 are 2942.46 ha or 15% of the total area of Nangapanda Subdistrict. Mostly, drought areas are located in the agricultural area and shrubs area. The increasing dry area can cause a decrease in the productivity of plantation commodities in Nangapanda.
KW - Dry area
KW - El Nino
KW - NDVI
KW - Plantation productivity
KW - TCT Wetness
UR - http://www.scopus.com/inward/record.url?scp=85113815363&partnerID=8YFLogxK
U2 - 10.1007/978-981-16-2329-5_19
DO - 10.1007/978-981-16-2329-5_19
M3 - Conference contribution
AN - SCOPUS:85113815363
SN - 9789811623288
T3 - Lecture Notes in Civil Engineering
SP - 171
EP - 183
BT - Sustainable Architecture and Building Environment - Proceedings of ICSDEMS 2020
A2 - Yola, Lin
A2 - Nangkula, Utaberta
A2 - Ayegbusi, Olutobi Gbenga
A2 - Awang, Mokhtar
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Sustainable Design, Engineering, Management, and Sciences, ICSDEMS 2020
Y2 - 8 December 2020 through 9 December 2020
ER -
