Classes for Spatial Data in R2.1 IntroductionMany disciplines have inf terjemahan - Classes for Spatial Data in R2.1 IntroductionMany disciplines have inf Bahasa Indonesia Bagaimana mengatakan

Classes for Spatial Data in R2.1 In

Classes for Spatial Data in R
2.1 Introduction
Many disciplines have influenced the representation of spatial data, both in
analogue and digital forms. Surveyors, navigators, and military and civil engineers
refined the fundamental concepts of mathematical geography, established
often centuries ago by some of the founders of science, for example by
al-Khw¯arizm¯ı. Digital representations came into being for practical reasons in
computational geometry, in computer graphics and hardware-supported gaming,
and in computer-assisted design and virtual reality. The use of spatial
data as a business vehicle has been spurred in the early years of the present
century by consumer broadband penetration and distributed server farms,
with a prime example being Google Earth™.1 There are often interactions between
the graphics hardware required and the services offered, in particular
for the fast rendering of scene views.
In addition, space and other airborne technologies have vastly increased
the volumes and kinds of spatial data available. Remote sensing satellites
continue to make great contributions to earth observation, with multi-spectral
images supplementing visible wavelengths. The Shuttle Radar Topography
Mission (SRTM) in February 2000 has provided elevation data for much of
the earth. Other satellite-borne sensor technologies are now vital for timely
storm warnings, amongst other things. These complement terrestrial networks
monitoring, for example lightning strikes and the movement of precipitation
systems by radar.
Surveying in the field has largely been replaced by aerial photogrammetry,
mapping using air photographs usually exposed in pairs of stereo
images. Legacy aerial photogrammetry worked with analogue images, and
many research laboratories and mapping agencies have large archives of
air photographs with coverage beginning from the 1930s. These images can
be scanned to provide a digital representation at chosen resolutions. While
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Classes for Spatial Data in R
2.1 Introduction
Many disciplines have influenced the representation of spatial data, both in
analogue and digital forms. Surveyors, navigators, and military and civil engineers
refined the fundamental concepts of mathematical geography, established
often centuries ago by some of the founders of science, for example by
al-Khw¯arizm¯ı. Digital representations came into being for practical reasons in
computational geometry, in computer graphics and hardware-supported gaming,
and in computer-assisted design and virtual reality. The use of spatial
data as a business vehicle has been spurred in the early years of the present
century by consumer broadband penetration and distributed server farms,
with a prime example being Google Earth™.1 There are often interactions between
the graphics hardware required and the services offered, in particular
for the fast rendering of scene views.
In addition, space and other airborne technologies have vastly increased
the volumes and kinds of spatial data available. Remote sensing satellites
continue to make great contributions to earth observation, with multi-spectral
images supplementing visible wavelengths. The Shuttle Radar Topography
Mission (SRTM) in February 2000 has provided elevation data for much of
the earth. Other satellite-borne sensor technologies are now vital for timely
storm warnings, amongst other things. These complement terrestrial networks
monitoring, for example lightning strikes and the movement of precipitation
systems by radar.
Surveying in the field has largely been replaced by aerial photogrammetry,
mapping using air photographs usually exposed in pairs of stereo
images. Legacy aerial photogrammetry worked with analogue images, and
many research laboratories and mapping agencies have large archives of
air photographs with coverage beginning from the 1930s. These images can
be scanned to provide a digital representation at chosen resolutions. While
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Kelas untuk Data Spasial di R
2.1 Pendahuluan
Banyak disiplin telah mempengaruhi representasi data spasial, baik dalam
bentuk analog dan digital. Surveyor, navigator, dan militer dan insinyur sipil
halus konsep dasar geografi matematika, didirikan
sering abad yang lalu oleh beberapa pendiri ilmu pengetahuan, misalnya dengan
al-Khawarizmi. Representasi digital muncul menjadi alasan praktis dalam
geometri komputasi, dalam komputer grafis dan game hardware didukung,
dan dalam desain dibantu komputer dan virtual reality. Penggunaan ruang
data sebagai kendaraan bisnis telah mendorong di tahun-tahun awal ini
abad oleh penetrasi broadband konsumen dan didistribusikan peternakan server,
dengan contoh utama menjadi Google Earth ™ 0,1 Ada sering interaksi antara
hardware grafis yang diperlukan dan layanan yang ditawarkan, khususnya
untuk rendering cepat penayangan adegan.
Selain itu, ruang dan teknologi udara lainnya telah jauh meningkat
volume dan jenis data spasial yang tersedia. Satelit deteksi jarak jauh
terus memberikan kontribusi besar untuk pengamatan bumi, dengan multi-spektral
gambar melengkapi panjang gelombang terlihat. Shuttle Radar Topografi
Mission (SRTM) pada bulan Februari 2000 telah memberikan data elevasi untuk banyak
bumi. Teknologi satelit-ditanggung lain sensor sekarang penting untuk tepat waktu
peringatan badai, antara lain. Ini melengkapi jaringan terestrial
pemantauan, untuk pemogokan misalnya petir dan gerakan presipitasi
sistem radar.
Survei di lapangan sebagian besar telah digantikan oleh foto udara,
pemetaan menggunakan foto udara biasanya terkena di pasang stereo
gambar. Legacy foto udara bekerja dengan gambar analog, dan
banyak laboratorium penelitian dan lembaga pemetaan memiliki arsip besar
foto udara dengan cakupan mulai dari tahun 1930-an. Gambar-gambar ini dapat
dipindai untuk memberikan representasi digital pada resolusi yang dipilih. Sementara
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