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Prof. Lilik Prasetyo
Bogor Agricultural University, Indonesia

Basic Info


Research Keywords & Expertise

0 Conservation
0 Landscape Ecology
0 Remote sensing & GIS applications
0 Spatial Modelling
0 forestry conservation

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Short Biography

Lilik Budi Prasetyo was born in Salatiga, in 1962. He completed his bachelor's degree from the Faculty of Agriculture – IPB University. While master (1993) and doctorate (1996) were received from the University of Tsukuba Japan, in the field of Environment science and Forest Management, respectively. Currently, he is Professor in Landscape Ecology, in the Department of Forest Resources Conservation and Ecotourism - Faculty of Forestry – IPB University. He is the head of the Environmental Analysis & Geospatial Modelling Laboratory, Chief Editor of Media Konservasi Journal and chairman of the working group for research on the LAPAN A3 Micro Satellite (LAPAN-IPB satellite/LISAT) application, principal investigator fo Forest2020 of Indonesia project funded by UKSA.

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Journal article
Published: 30 April 2021 in Media Konservasi
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The forest inventory technique by applying remote sensing technology has become a new breakthrough in technological developments in forest inventory activities. Unmanned Aerial Vehicle (UAV) imagery with camera sensor is one of the inventory tools that produce data with high spatial resolution. The level of spatial resolution of the image is strongly influenced by the flying height of the UAV for a certain camera’s focus. In addition, flight height also affects the acquisition time and accuracy of inventory results, although there is still little research on this matter. The study aims to (a)evaluate the effect of various flying heights on the accuracy of tree height measurements through UAV imagery for every stand age class, (b).estimate the trees diameter and canopy cover for every stand age class. Stand height was estimated using Digital Surface Models (DSM), Digital Terrain Models (DTM) and Orthophoto. DSM and DTM were built by converting orthophoto to pointclouds using the PIX4Dmapper based on Structure From Motion (SFM) on the photogrammetric method to reconstruct topography automatically. Meanwhile, the tree cover canopy was estimated using the All Return Canopy Index (ARCI) formula. The results show that the flight height of 100 meters produces a stronger correlation than the flying height of 80 meters and 120 meters in estimating tree height, based on the high coefficient of determination (R2) and the low root mean square error (RMSE) value. In addition, tree canopy estimation analysis using ARCI has a maximum difference of 9.8% with orthophoto visual delineation. Key words: canopy height model (CHM), digital surface models (DSM), digital terrain models (DTM), forest inventory, UAV image

ACS Style

Muflihatul Maghfiroh Islami; Teddy Rusolono; Yudi Setiawan; Aswin Rahadian; Sahid Agustian Hudjimartsu; Lilik Budi Prasetyo. HEIGHT, DIAMETER AND TREE CANOPY COVER ESTIMATION BASED ON UNMANNED AERIAL VEHICLE (UAV) IMAGERY WITH VARIOUS ACQUISITION HEIGHT. Media Konservasi 2021, 26, 17 -27.

AMA Style

Muflihatul Maghfiroh Islami, Teddy Rusolono, Yudi Setiawan, Aswin Rahadian, Sahid Agustian Hudjimartsu, Lilik Budi Prasetyo. HEIGHT, DIAMETER AND TREE CANOPY COVER ESTIMATION BASED ON UNMANNED AERIAL VEHICLE (UAV) IMAGERY WITH VARIOUS ACQUISITION HEIGHT. Media Konservasi. 2021; 26 (1):17-27.

Chicago/Turabian Style

Muflihatul Maghfiroh Islami; Teddy Rusolono; Yudi Setiawan; Aswin Rahadian; Sahid Agustian Hudjimartsu; Lilik Budi Prasetyo. 2021. "HEIGHT, DIAMETER AND TREE CANOPY COVER ESTIMATION BASED ON UNMANNED AERIAL VEHICLE (UAV) IMAGERY WITH VARIOUS ACQUISITION HEIGHT." Media Konservasi 26, no. 1: 17-27.

Review
Published: 29 April 2021 in Land
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Indonesia has experienced one of the world’s greatest dynamic land changes due to forestry and agricultural practices. Understanding the drivers behind these land changes remains challenging, partly because landscape research is spread across many domains and disciplines. We provide a systematic review of 91 studies that identify the causes and land change actors across Sumatra and Kalimantan. Our review shows that oil palm expansion is the most prominent (65 studies) among multiple direct causes of land change. We determined that property rights are the most prominent issue (31 studies) among the multiple underlying causes of land change. Distinct combinations of mainly economic, institutional, political, and social underlying drivers determine land change, rather than single key drivers. Our review also shows that central and district governments as decision-making actors are prominent (69 studies) among multiple land change actors. Our systematic review indicates knowledge gaps that can be filled by clarifying the identification and role of actors in land change.

ACS Style

Lila Juniyanti; Herry Purnomo; Hariadi Kartodihardjo; Lilik Prasetyo. Understanding the Driving Forces and Actors of Land Change Due to Forestry and Agricultural Practices in Sumatra and Kalimantan: A Systematic Review. Land 2021, 10, 463 .

AMA Style

Lila Juniyanti, Herry Purnomo, Hariadi Kartodihardjo, Lilik Prasetyo. Understanding the Driving Forces and Actors of Land Change Due to Forestry and Agricultural Practices in Sumatra and Kalimantan: A Systematic Review. Land. 2021; 10 (5):463.

Chicago/Turabian Style

Lila Juniyanti; Herry Purnomo; Hariadi Kartodihardjo; Lilik Prasetyo. 2021. "Understanding the Driving Forces and Actors of Land Change Due to Forestry and Agricultural Practices in Sumatra and Kalimantan: A Systematic Review." Land 10, no. 5: 463.

Journal article
Published: 31 March 2021 in Jurnal Penelitian Kehutanan Wallacea
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Bekantan (Nasalis larvatus) adalah satwa primata langka dilindungi yang populasinya terus mengalami penurunan akibat hilang dan rusaknya habitat. Delta Berau adalah salah satu lokasi penyebaran bekantan yang berada di luar kawasan konservasi yang kurang mendapat perhatian. Penelitian ini bertujuan untuk mengetahui populasi dan sebaran bekantan di Delta Berau dan sekitarnya. Perhitungan populasi dilakukan secara langsung dari sungai (boat survey) pada pagi dan sore hari. Hasil penelitian menunjukkan terdapat 1.350-1.774 ekor bekantan yang terbagi dalam 115 kelompok satu-jantan, 5 kelompok semua-jantan, 1 soliter, dan 5 kelompok tidak teridentifikasi. Faktor koreksi sebagai pengali populasi tertinggi pada habitat riparian dan mangrove masing-masing sebesar 1,33 dan 1,27. Kepadatan populasi bekantan secara umum adalah 6,56 ekor/km2 (kisaran: 0,91-93,33) atau 0,59 kelompok/km2 (kisaran: 0,13-9,17). Nisbah kelamin kelompok satu-jantan pada tipe habitat riparian dan habitat mangrove masing-masing sebesar 1:5,6 dan 1:6,1. Sebaran bekantan tertinggi berada di wilayah Kampung Pulau Besing (Pulau Besing, Pulau Bungkung, dan Pulau Sambuayan), yaitu sebanyak 42 kelompok 426 ekor atau sebesar 32% dari total populasi bekantan. Populasi bekantan yang tinggi menunjukkan bahwa Delta Berau adalah habitat penting bagi bekantan di Indonesia. Inisiasi pengelolaan habitat bekantan sebagai Kawasan Ekosistem Esensial (KEE) diperlukan, selain perlindungan bekantan secara lokal oleh masyarakat adat setempat sekaligus sebagai upaya melindungi sumber daya perikanan di sekitarnya.

ACS Style

Tri Atmoko; Ani Mardiastuti; Muhammad Bismark; Lilik Budi Prasetyo; Entang Iskandar. Populasi dan sebaran bekantan (Nasalis larvatus) di Delta Berau. Jurnal Penelitian Kehutanan Wallacea 2021, 10, 11 -23.

AMA Style

Tri Atmoko, Ani Mardiastuti, Muhammad Bismark, Lilik Budi Prasetyo, Entang Iskandar. Populasi dan sebaran bekantan (Nasalis larvatus) di Delta Berau. Jurnal Penelitian Kehutanan Wallacea. 2021; 10 (1):11-23.

Chicago/Turabian Style

Tri Atmoko; Ani Mardiastuti; Muhammad Bismark; Lilik Budi Prasetyo; Entang Iskandar. 2021. "Populasi dan sebaran bekantan (Nasalis larvatus) di Delta Berau." Jurnal Penelitian Kehutanan Wallacea 10, no. 1: 11-23.

Journal article
Published: 15 February 2021 in Biology
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Indonesia has a large number of primate diversity where a majority of the species are threatened. In addition, climate change is conservation issues that biodiversity may likely face in the future, particularly among primates. Thus, species-distribution modeling was useful for conservation planning. Herein, we present protected areas (PA) recommendations with high nature-conservation importance based on species-richness changes. We performed maximum entropy (Maxent) to retrieve species distribution of 51 primate species across Indonesia. We calculated species-richness change and range shifts to determine the priority of PA for primates under mitigation and worst-case scenarios by 2050. The results suggest that the models have an excellent performance based on seven different metrics. Current primate distributions occupied 65% of terrestrial landscape. However, our results indicate that 30 species of primates in Indonesia are likely to be extinct by 2050. Future primate species richness would be also expected to decline with the alpha diversity ranging from one to four species per 1 km2. Based on our results, we recommend 54 and 27 PA in Indonesia to be considered as the habitat-restoration priority and refugia, respectively. We conclude that species-distribution modeling approach along with the categorical species richness is effectively applicable for assessing primate biodiversity patterns.

ACS Style

Aryo Condro; Lilik Prasetyo; Siti Rushayati; I Santikayasa; Entang Iskandar. Predicting Hotspots and Prioritizing Protected Areas for Endangered Primate Species in Indonesia under Changing Climate. Biology 2021, 10, 154 .

AMA Style

Aryo Condro, Lilik Prasetyo, Siti Rushayati, I Santikayasa, Entang Iskandar. Predicting Hotspots and Prioritizing Protected Areas for Endangered Primate Species in Indonesia under Changing Climate. Biology. 2021; 10 (2):154.

Chicago/Turabian Style

Aryo Condro; Lilik Prasetyo; Siti Rushayati; I Santikayasa; Entang Iskandar. 2021. "Predicting Hotspots and Prioritizing Protected Areas for Endangered Primate Species in Indonesia under Changing Climate." Biology 10, no. 2: 154.

Journal article
Published: 06 November 2020 in Biodiversitas Journal of Biological Diversity
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Repi T, Masy’ud B, Mustari AH, Prasetyo LB. 2020. Population density, geographical distribution and habitat of Talaud bear cuscus (Ailurops melanotis Thomas, 1898). Biodiversitas 21: 5621-5631. The Talaud bear cuscus (Ailurops melanotis) has been reported from Sangihe (the largest island in the Sangihe Island group) and Salibabu (within the Talaud Islands). As an endemic species of Indonesia, this species is rare and there is no certainty regarding its precise geographic distribution or population size. This research aimed to estimate population density and provide the first preliminary data on its geographical distribution, as well as general description of its habitat. Our research shows that A. melanotis occurs on three islands: Salibabu Island, Nusa Island, and Bukide Island, and probably also exists in the Sahandaruman mountain on Sangihe Island. Our population surveys estimate, population density on each island as: Salibabu: 3.69 ± 2.54 ind/km2, with an estimated total population of 28.95 individuals, Nusa Island: was 12.31 ± 2.58 ind/km2, with an estimated population of 19.08 individuals, and Bukide Island: 7.17 ± 1.79/km2, with an estimated population of 10.40 individuals. Information regarding population is a key guiding factor in conservation efforts, where population size is related to extinction risk (threat status) and its geographical distribution, this can help to determine conservation priorities for species or habitats.

ACS Style

Terri Repi; Burhanuddin Masy’Ud; Abdul Haris Mustari; Lilik Budi Prasetyo. Population density, geographical distribution and habitat of Talaud bear cuscus (Ailurops melanotis Thomas, 1898). Biodiversitas Journal of Biological Diversity 2020, 21, 1 .

AMA Style

Terri Repi, Burhanuddin Masy’Ud, Abdul Haris Mustari, Lilik Budi Prasetyo. Population density, geographical distribution and habitat of Talaud bear cuscus (Ailurops melanotis Thomas, 1898). Biodiversitas Journal of Biological Diversity. 2020; 21 (12):1.

Chicago/Turabian Style

Terri Repi; Burhanuddin Masy’Ud; Abdul Haris Mustari; Lilik Budi Prasetyo. 2020. "Population density, geographical distribution and habitat of Talaud bear cuscus (Ailurops melanotis Thomas, 1898)." Biodiversitas Journal of Biological Diversity 21, no. 12: 1.

Journal article
Published: 08 October 2020 in Land
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Indonesia has the most favorable climates for agriculture because of its location in the tropical climatic zones. The country has several commodities to support economics growth that are driven by key export commodities—e.g., oil palm, rubber, paddy, cacao, and coffee. Thus, identifying the main commodities in Indonesia using spatially-explicit tools is essential to understand the precise productivity derived from the agricultural sectors. Many previous studies have used predictions developed using binary maps of general crop cover. Here, we present national commodity maps for Indonesia based on remote sensing data using Google Earth Engine. We evaluated a machine learning algorithm—i.e., Random Forest to parameterize how the area in commodity varied in Indonesia. We used various predictors to estimate the productivity of various commodities based on multispectral satellite imageries (36 predictors) at 30-meters spatial resolution. The national commodity map has a relatively high accuracy, with an overall accuracy of about 95% and Kappa coefficient of about 0.90. The results suggest that the oil palm plantation was the highest commodity product that occupied the largest land of Indonesia. However, this study also showed that the land area in rubber, rice paddies, and cacao commodities was underestimated due to its lack of training samples. Improvement in training data collection for each commodity should be done to increase the accuracy of the commodity maps. The commodity data can be viewed online (website can be found in the end of conclusions). This data can further provide significant information related to the agricultural sectors to investigate food provisioning, particularly in Indonesia.

ACS Style

Aryo Condro; Yudi Setiawan; Lilik Prasetyo; Rahmat Pramulya; Lasriama Siahaan. Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform. Land 2020, 9, 377 .

AMA Style

Aryo Condro, Yudi Setiawan, Lilik Prasetyo, Rahmat Pramulya, Lasriama Siahaan. Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform. Land. 2020; 9 (10):377.

Chicago/Turabian Style

Aryo Condro; Yudi Setiawan; Lilik Prasetyo; Rahmat Pramulya; Lasriama Siahaan. 2020. "Retrieving the National Main Commodity Maps in Indonesia Based on High-Resolution Remotely Sensed Data Using Cloud Computing Platform." Land 9, no. 10: 377.

Conference paper
Published: 01 November 2017 in 2017 European Modelling Symposium (EMS)
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Automated classification algorithms for satellite imageries require spectral correction from terrain effects due to shading. Such terrain effects can produce reflectance bias of pixels in the same category. This study was aimed at exploring robust algorithms for correcting satellite imageries from terrain effects, applicable for either Landsat 8 or Sentinel-2A imageries. Mount Halimun-Salak and Mount Gede-Pangrango, Bogor, West Java, Indonesia, were selected as the window areas to evaluate the algorithm. We developed algorithm, which combined solar position modelling, illumination modelling, and simple statistical model to remove the terrain effects. The algorithm was proven to be able to solve over correction problems and result relatively consistent sensitivities in SWIR, NIR and blue bands of either Landsat 8 or Sentinel-2A imageries in both window areas from different acquisition dates and times.

ACS Style

Sahid Hudjimartsu; Lilik Prasetyo; Yudi Setiawan; Desi Suyamto. Illumination Modelling for Topographic Correction of Landsat 8 and Sentinel-2A Imageries. 2017 European Modelling Symposium (EMS) 2017, 95 -99.

AMA Style

Sahid Hudjimartsu, Lilik Prasetyo, Yudi Setiawan, Desi Suyamto. Illumination Modelling for Topographic Correction of Landsat 8 and Sentinel-2A Imageries. 2017 European Modelling Symposium (EMS). 2017; ():95-99.

Chicago/Turabian Style

Sahid Hudjimartsu; Lilik Prasetyo; Yudi Setiawan; Desi Suyamto. 2017. "Illumination Modelling for Topographic Correction of Landsat 8 and Sentinel-2A Imageries." 2017 European Modelling Symposium (EMS) , no. : 95-99.