Dyah Retno Panuju

Comparing six pixel-wise classifiers for tropical rural land cover mapping using four forms of fully polarimetric SAR data

ABSTRACT This study evaluates four commonly used forms of synthetic aperture radar (SAR) data for land-cover classification in tropical rural areas. The backscatter coefficient of linearly polarized L-band SAR was compared to two distinctive feature sets derived from Eigen-based and model-based decompositions. The performance of six classifiers available in Orfeo Toolbox (OTB), that is, Bayes, artificial neural networks (ANNs), Support Vector Machine (SVM), decision trees, Random Forests (RFs), and gradient boosting trees (GBTs), was investigated to distinguish five and seven land-cover classes, with particular attention given to several types of woody vegetation: forest, mixed garden, rubber, oil palm, and tea plantations. Classifiers reacted differently to ingested forms of SAR data, and careless use of data input yielded a negative impact. The results showed that SVM provided the highest overall accuracy although the performance was not significantly better than the others. Tuning the parameters, however, significantly improved the accuracy of ANN and SVM, while RF and GBT did not respond well. Responses of two SVM parameters (cost and kernel type) fluctuated somewhat, which required further attention. ANN accuracy was improved when the number of neurons in the hidden layer was set between 10 and 12. We found that accuracy imbalance existed between designated land-cover classes, especially in woody vegetation. Imbalance can partially be reduced by tuning specific classifiers. We showed that classifier tuning can lead to significantly improved accuracy, especially for classes having medium or low accuracies. This research also demonstrated that freely available toolkits such as OTB and QGIS can be beneficial for mapping activities in developing countries, achieving a reasonable accuracy if the classification parameters are tuned properly.

Interferometric processing of C-band SAR data for the improvement of stand age estimation in rubber plantation

Rubber ranks the second largest plantation in Indonesia after oil palm. While oil palm plantations have been exploited mainly by large companies, many rubber plantations are still managed by peasant farmers who maintain its biodiversity. Due to its broad and scattered location, monitoring tropical rubber plantation is a crucial application of active remote sensing. In this paper, the backscatter coefficient of Envisat Advanced Synthetic Aperture Radar (ASAR) is compared to interferometric coherence to study the relationship between stand age and SAR parameters. It is shown that VV polarized C-band SAR achieves its saturation level in plantations aged about 5-10 years. Extension of saturation level can be achieved by processing an interferometric pair of ASAR data, which results in interferometric coherence. In this paper, coherence can take up to 20 years stand age to achieve prior to saturation. Since stand age is highly related to biomass, this finding argues that the biomass can be best estimated using coherence.

IDENTIFIKASI KOMODITAS BASIS TANAMAN PANGAN DAN ARAHAN PENGEMBANGANNYA DI PROVINSI LAMPUNG

Pengembangan wilayah pertanian saat ini banyak dilakukan tanpa penelitian terlebih dahulu dari keunggulan komparatif, kompetitif dan potensi sumberdaya lahan pertanian. Tujuan dari penelitian ini adalah: (1) Mengetahui komoditas basis tanaman pangan yang memiliki keunggulan komparatif dan kompetitif di Provinsi Lampung, (2) mengevaluasi kesesuaian lahan komoditas basis, (3) menganalisis hubungan antara komoditas basis dengan kesesuaian lahan, dan (4) menyusun arahan pengembangan komoditas basis. Metode penelitian yang digunakan dalam mengidentifikasi keunggulan komparatif adalah perhitungan Location Quotient (LQ). Identifikasi keunggulan kompetitif dilakukan menggunakan komponen Differential Shift (DS). Evaluasi kesesuaian lahan dilakukan dengan membandingkan karakteristik tanah dengan kriteria tumbuh tanaman. Analisis korelasi digunakan untuk menganalisis keterkaitan antara komoditas basis dengan tingkat kesesuaian lahan. Hasil penelitian menunjukkan adanya komoditas basis tanaman pangan di masing-masing kabupaten, kecuali di 3 kabupaten yaitu Kabupaten Tulangbawang, Tulang Bawang Barat dan Mesuji yang tidak memiliki komoditas basis. Kesesuaian lahan aktual untuk tanaman komoditas basis di masing-masing kabupaten juga telah dihasilkan. Tanaman padi sawah banyak ditanam di lahan yang cukup sesuai di sebagian besar kabupaten. Pengusahaan masing-masing komoditas basis dikaitkan dengan tingkat kesesuaian lahannya di masing-masing kabupaten juga dikemukakan. Demikian juga arahan pengembangan masing-masing komoditas basis dan luasannya di masing-masing kabupaten. Lahan pada kawasan budidaya pertanian yang tergolong tidak sesuai disarankan digunakan sebagai kawasan konservasi.

IDENTIFIKASI LAHAN TERSEDIA DENGAN TEKNOLOGI INFORMASI SPASIAL UNTUK MENDUKUNG REFORMA AGRARIA: STUDI KASUS PROVINSI RIAU DAN JAWA BARAT

Pemerintah khususnya Badan Pertanahan Nasional meluncurkan program pemerintah yang dinamai dengan Reforma Agraria Plus. Program reforma agraria tersebut mempertimbangkan berbagai kriteria lahan antara lain kualitas dan ketersediaan lahan, variabel akses pasar untuk pemanfaatan lahan yang optimum. Salah satu bentuk reforma agraria plus adalah program redistribusi lahan. Percepatan redistribusi lahan dapat dilakukan jika proses identifikasi lahan tersedia memanfaatkan teknologi informasi spasial untuk efisiensi waktu dan cakupan area. Penelitian ini bertujuan untuk menguji pilihan variabel penting untuk mengidentifikasi lahan tersedia untuk alokasi program reforma agraria. Penelitian dilakukan di Provinsi Riau dan Jawa Barat. Identifikasi lahan tersedia diawali dengan penyusunan database. Selanjutnya berdasarkan kriteria status kawasan, kesesuaian fisik, status penguasaan, dan penutupan lahan, luas lahan ditapis dengan metode evaluasi kriteria jamak dan dua alternatif. Alternatif-1 adalah kriteria ideal yaitu tingkat kesesuaian minimum S3, bukan lahan HGU, penggunaan untuk pertanian dan bukan kawasan lindung serta dekat jalan; dan alternatif-2 sama dengan alternatif-1 kecuali penguasaan HGU dalam waktu dekat (< 5 tahun) habis. Luas lahan yang diperoleh didistribusikan ke masyarakat petani/nelayan berlahan sempit. Hasil penelitian menunjukan penerapan kombinasi variabel terpilih yang berbeda dalam proses filter menghasilkan luasan berbeda. Hasil identifikasi luas lahan tersedia untuk alokasi program reforma agraria di Jawa Barat dan Riau menunjukkan bahwa kebutuhan hidup minimum masyarakat kedua lokasi berbeda. Perbedaan standar kebutuhan hidup minimum dan struktur harga serta tingkat kesuburan wilayah berimplikasi pada perbedaan luas lahan minimum bagi petani. Petani di Jawa Barat membutuhkan lahan lebih kecil untuk memenuhi kebutuhan hidup dibandingkan petani di Riau. Lahan tersedia di Riau menyebar di seluruh kabupaten/kota, sedangkan di Jawa Barat beberapa kabupaten tidak terdapat lahan tersedia untuk alokasi khususnya di wilayah Kabupaten Bekasi, Cirebon, Indramayu, dan kota Depok.

Characteristics of L-band backscatter coefficients of rubber plantation and their seasonal dynamics

As one of primary land uses in Indonesia, rubber plantation requires frequent, wide-scale monitoring. Due to the nature of tropical region, optical sensors are often inapplicable and therefore Synthetic Aperture Radar (SAR) plays a role. Dual-polarized SAR data have been a definitive imaging mode since fully polarimetric mode consumes higher energy. In this paper, characteristics of returning SAR signals from young rubber stands are investigated in terms of different polarization and time of acquisition. The research shows that strong ground attenuation is observed in very young plantation, which is similar to amplified Bragg scattering in rice field. Seasonal defoliation is also evident at this age, possibly due to limited root depth which reduces ability to obtain moisture in lower solum. Temporal change of canopy cover is detectable by HV polarization, which has been known sensitive to canopy structure. This research suggests that seasonal variation of HV backscatter coefficients may affect biophysical...

Seasonal Pattern of Vegetative Cover from NDVI Time-Series

Indonesia manages various forested land utilizations, for instance natural forest and plantations. In the past, natural forest had been exploited throughout the country, mainly in the islands of Sumatera and Borneo (Nawir & Rumboko, 2007). Greater criticisms on forest exploitation lead to a moratorium which needs to be monitored frequently. Most of forest concessions were converted into plantations (Kartodihardjo & Supriono, 2000). Popular plantations developed in the country have been rubber and oil palm. Successful management of the plantation as well as natural forest has been under careful examination. Assessment of woody vegetation could be taken using field surveys or remote sensing. Although having possibilities to capture detailed datasets, field survey is lacking in terms of implementation: lengthy data capture and least favorable to remote areas. In these situations, remotely sensed data play a crucial role.